Hassan Al Majou

Ary Bruand
email: ary.bruand@univ-orleans.fr

Odile Duval

Isabelle Cousin

Variation of the water retention properties of soils: Validity of class-pedotransfer functions Variation des propriétés de rétention en eau des sols : Validité des classes de pédotransfert

Keywords: Texture, Bulk density, Horizon, Structure, Prediction bias, Prediction precision Résumé Texture, Densité apparente, Horizon, Structure, Biais de prédiction, Précision

Water retention properties of soils vary according to soil characteristics and understanding of their variation remains controversial. Numerous pedotransfer functions (ptfs) that enable prediction of the water retention properties of soils were developed but their validity was poorly discussed. In this study we compare the performance of textural and texturo-structural class-ptfs with more sophisticated class-and continuous-ptfs developed using the same set of soils. We showed that the former led to prediction performance that are better or similar to those recorded with the more sophisticated class-and continuous-ptfs studied. Thus, textural and texturo-structural class-ptfs that are quite easy to establish are potentially worthwhile tools for predicting the water retention properties of soils, particularly at scales for which semi-quantitative or qualitative basic soil characteristic such as the texture are the only characteristic available. More generally, our results pointed out that the discussion of ptfs performance should refer to those recorded with easy to establish ptfs, thus enabling to quantify how much prediction bias and precision can be gained when increasing the complexity of ptfs and consequently the number and quality of predictors required.

Introduction

Understanding of soil water retention properties of soil remains a major issue in soil science.

Because of the growing demand for soil hydraulic properties, a common solution has been to use pedotransfer functions (ptfs) that relate basic soil properties that are considered as easily accessible to the less often measured soil properties such as hydraulic properties [START_REF] Bouma | Transfer functions and threshold values: from soil characteristics to land qualities[END_REF]. A huge number of ptfs was developed over the last three decades and we are facing today to the continuous development of ptfs of increasing complexity with very little or no information about the potential increase in the prediction quality. There is some information available about the performance of continuous-ptfs [START_REF] Minasmy | Comparison of different approaches to the development of pedotransfer functions for water-retention curves[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF], very little about the performance of classptfs [START_REF] Ungaro | Development of pedotransfer functions using a group method of handling for the soil of the Pianura Padano -Veneta region of North Italy: water retention properties[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF] and less again about the compared performance of these two types of ptfs [START_REF] Wösten | Comparison of class and continuous pedotransfer functions to generate soil hydraulic characteristics[END_REF].

The aim of this study is to show that variation of water retention properties can be predicted by using stratification based on information about particle size distribution and structure. We show also that the quality of the prediction is similar or better than with much more sophisticated ptfs despite what is usually admitted.

Materials and methods

The ptfs developed in the literature

Most ptfs published in the literature are continuous-pedotransfer functions (continuous-ptfs), i.e. mathematical continuous functions between the water content at discrete values of potential or the parameters of a unique model of water retention curve and the basic soil properties (mostly particle size distribution, organic carbon content and bulk density) [START_REF] Pachepsky | Hydropedology and pedotransfer functions[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF].

Besides these continuous-ptfs that enable continuously the prediction of water content at particular water potentials [START_REF] Rawls | Estimation of soil water properties[END_REF] or estimation of the parameters of models of the water retention curve [START_REF] Cresswell | The transferability of Australian pedotransfer functions for predicting water retention characteristics of French soils[END_REF][START_REF] Minasmy | Comparison of different approaches to the development of pedotransfer functions for water-retention curves[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF], there are class pedotransfer functions (class-ptfs) that received little attention because their accuracy is considered as limited [START_REF] Wösten | Comparison of class and continuous pedotransfer functions to generate soil hydraulic characteristics[END_REF]. The existing class-ptfs provide often average water contents at particular water potentials or one average water retention curve for every texture class [START_REF] Bruand | Use of class pedotransfer functions based on texture and bulk density of clods to generate water retention curves[END_REF][START_REF] Nemes | Functions evaluation of pedotransfer functions derived from different scales of data collection[END_REF]. Due to the range in particle size distribution, clay mineralogy, organic matter content and structural development within each texture class, water retention properties for individual soils were considered as varying considerably [START_REF] Wösten | Development and use of a database of hydraulic properties of European soils[END_REF].

Despite their possible inaccuracies, class-ptfs enable the prediction based on successive stratification using soil characteristics. Moreover, class-ptfs are easy to use because they require little soil information and are well adapted to the prediction of water retention properties over large areas [START_REF] Lilly | The development and use of the HYPRES database in Europe[END_REF][START_REF] Wösten | Comparison of class and continuous pedotransfer functions to generate soil hydraulic characteristics[END_REF][START_REF] Wösten | Development and use of a database of hydraulic properties of European soils[END_REF]. There is some information available about the performance of continuous-ptfs [START_REF] Minasmy | Comparison of different approaches to the development of pedotransfer functions for water-retention curves[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF], very little about the performance of class-ptfs [START_REF] Ungaro | Development of pedotransfer functions using a group method of handling for the soil of the Pianura Padano -Veneta region of North Italy: water retention properties[END_REF][START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF] and less again about the compared performance of these two types of ptfs [START_REF] Wösten | Comparison of class and continuous pedotransfer functions to generate soil hydraulic characteristics[END_REF].

The soils studied

Class-and continuous-ptfs were developed using a set of 320 horizons comprising 90 topsoils (from 0 to 30 cm depth) and 230 subsoil horizons (>30 cm depth) collected in Cambisols, Luvisols, Planosols, Albeluvisols, Podzols and Fluvisols [START_REF]World Reference Base for Soil Resources: Introduction[END_REF] located mainly in the Paris basin and secondarily in the western coastal marshlands and Pyrenean piedmont plain. A set of 107 horizons comprising 39 topsoil and 68 subsoil horizons was constituted in order to test the ptfs established. These horizons were collected in Cambisols, Luvisols and Fluvisols [START_REF]World Reference Base for Soil Resources: Introduction[END_REF] located in the South of the Paris basin. Basic characteristics and water retention properties of the horizons were determined as earlier described by Bruand and Tessier [START_REF] Bruand | Water retention properties of the clay in soils developed on clayey sediments: Significance of parent material and soil history[END_REF] (Figure 1, Table 1). Their bulk density (D b ) was measured by using cylinders 1000 cm 3 in volume when the soil was near to field capacity.

Analysis of the PTFs performance

In order to discuss the global validity of the ptfs, most studies used the root mean square error (RMSE) that is also called root mean squared deviation or root mean square residual [START_REF] Wösten | Pedotransfer functions: bridging the gap between available basic soil data missing soil hydraulic characteristics[END_REF].

Because the RMSE varies according to both the prediction bias and precision, we computed the mean error of prediction (MEP) that enables discussion of the prediction bias alone on one hand and the standard deviation of prediction (SDP) that enables discussion of the prediction precision alone on the other hand. We computed MEP and SDP for the whole water potentials as follows:

∑ ∑ = = - ⋅ = l i i j m i j p l j l l MEP 1 , , , , ' 1 ' ) ( 1 θ θ [ ] 2 / 1 1 2 , , , , ' 1 ' ) ( 1       - - ⋅ = ∑ ∑ = = l i i j m i j p l j MEP l l SDP θ θ
where θ p,j,i is the predicted water content at potential i for the horizon j, θ m,i,j is the measured water content at potential i for the horizon j, and l is the number of water potentials for each horizon (l=7 in this study) and l' is the number of horizons (l' ≤ 107 in this study). The MEP corresponds to the bias and indicates whether the ptfs overestimated (positive) or underestimated (negative) the water content, whereas SDP measures the precision of the prediction.

In order to discuss the validity of the ptfs at the different water potentials we computed also the mean error of prediction (MEP') and the standard deviation (SDP') of prediction at every water potential as follows:

( ) ∑ = - = ' 1 , , ' ' 1 l j j m j p l MEP θ θ ( ) [ ] 2 / 1 2 ' 1 ' , , ' ' 1           - - = ∑ = l j j m j p MEP l SDP θ θ .

Results and discussion

The class-and continuous-ptfs developed

The class-ptfs developed in this Note were established according to the texture (textural classptfs) in the CEC triangle [START_REF]Commission of the European Communities (CEC), Soil map of the European Communities[END_REF] and then according to both that texture and D b (texturo-structural class-ptfs). The resulting class-ptfs corresponded to the average water content at 7 water potentials that was computed within every class of texture (textural class-ptfs) (Table 2) and every class combining both texture and D b (texturo-structural class-ptfs) (Table 3). More complex class-ptfs were established by fitting the van Genuchten's model [START_REF] Van Genuchten | A closed-form equation for predicting the hydraulic conductivity of unsaturated soil[END_REF] on the arithmetic mean value of θ at the different values of water potential using the RETC code [START_REF] Van Genuchten | The RETC code for quantifying the hydraulic functions of unsaturated soils[END_REF] for every class of texture (VG texture class-ptfs) according to the CEC triangle [START_REF]Commission of the European Communities (CEC), Soil map of the European Communities[END_REF] and the type of horizon (topsoil and subsoil) (Table 4).

Continuous-ptfs were also developed. They correspond to multiple regression equations as follows:

θ = a + (b×%Cl) + (c×%Si) + (d×%OC) + (e×D b )
with θ, the volumetric water content at a given water content, a, b, c and e the regression coefficients, %Cl and %Si, respectively the clay and silt content, %OC, the organic carbon content and D b , the bulk density (Table 5). Other continuous-ptfs were developed as earlier done by Wösten et al. [START_REF] Wösten | Development and use of a database of hydraulic properties of European soils[END_REF] for the parameters of the van Genuchten's model using multiple regression equations (VG continuous-ptfs) (Table 6). For every horizon, the parameters of the van Genuchten's model were computed using the RETC code [START_REF] Van Genuchten | The RETC code for quantifying the hydraulic functions of unsaturated soils[END_REF].

Validity of the class-ptfs

The textural class-ptfs underestimated very slightly the water retained (MEP = -0.003 cm 3 cm -3 ) when they are applied to the test dataset without any other stratification than according to the texture. There was no decrease in the prediction bias with the texturostructural class-ptfs (MEP = -0.004 cm 3 cm -3 ) but the bias was already very small with the textural class-ptfs studied. However the precision was slightly better with the texturostructural class-ptfs (SDP = 0.043 cm 3 cm -3 ) than with the textural class-ptfs (SDP = 0.045 cm 3 cm -3 ) (Figure 2a andb). Compared to the textural class-ptfs, the VG textural class-ptfs showed similar performance. The bias was very small (MEP = 0.002 cm 3 cm -3 ) and the precision poor (SDP = 0.045 cm 3 cm -3 ) as recorded for the textural class-ptfs (Figure 2c). The comparison of the class-ptfs performance at every value of water potential showed small bias (-0.008 ≤ MEP' ≤ 0.007 cm 3 cm -3 ) except for θ 4.2 for the textural and texturo-structural classptfs (MEP' = -0.020 and -0.019 cm 3 cm -3 ) and for θ 1.0 for the VG Class-ptfs (MEP' = 0.014 cm 3 cm -3 ) for which it was greater (Table 7). This comparison showed also poor precision for the three class-ptfs studied whatever the water potential (0.040 ≤ SDP' ≤ 0.047 cm 3 cm -3 ).

Validity of the continuous-ptfs

When applied to the test data set, the continuous-ptfs leads to very small bias (MEP = -0.003 cm 3 cm -3 ) and showed poor precision (SDP = 0.039 cm 3 cm -3 ). Results showed a greater bias with the VG continuous-ptfs (MEP = -0.008 cm 3 cm -3 ) and similar poor precision (SDP = 0.039 cm 3 cm -3 ) than with the continuous-ptfs (Figure 2d ande). The comparison of the continuous-ptfs performance at every value of water potential showed small bias for the continuous-ptfs (-0.006 ≤ MEP' ≤ 0.005 cm 3 cm -3 ) except for θ 4.2 (MEP' = -0.022 cm 3 cm -3 ).

For the VG continuous-ptfs the bias was greater for six water potentials with absolute value of MEP' ≤ 0.020 cm 3 cm -3 except for θ 1.5 (MEP' = 0.004 cm 3 cm -3 ) (Table 7). The precision was poor for the simple and VG Continuous-ptfs (0.030 ≤ SDP' ≤ 0.044 cm 3 cm -3 ) but results showed that SDP decreased with the water potential.

Comparison of the class-and continuous-ptfs

Results showed very little difference between the ptfs studied. The bias recorded was small (-0.008 ≤ MEP ≤ 0.002 cm 3 .cm -3 ) and the greatest absolute value of bias was recorded with the VG continuous-ptfs (MEP = -0.008 cm 3 .cm -3 ). On the other hand, the precision was poor (0.039 ≤ SDP ≤ 0.045 cm 3 .cm -3 ), the greatest precision being recorded with the two types of continuous-ptfs studied. If the VG Continuous-ptfs led to the greatest precision (SDP = 0.039 cm 3 .cm -3 ), they led also the greatest value of bias (MEP = -0.008 cm 3 .cm -3 ).

Conclusion

Our results showed that textural class-ptfs led to prediction performance that are similar to those recorded with more sophisticated class-ptfs and with continuous-ptfs. Thus without knowing the particle size distribution, organic carbon content and bulk density as required by most ptfs, we can predict the water retention properties with similar prediction quality by using the texture alone. Our results showed also that use of both texture and bulk density slightly increase the precision when compared to the precision recorded with the textural class-ptfs. Finally, we showed also that class-ptfs, including very simple ptfs, should be still considered as useful tools for predicting the water retention properties of soils, particularly at scales for which semi-quantitative or qualitative basic soil characteristic such as the texture are the only characteristic available. More generally, our results pointed out that discussion of ptfs performance should refer to those recorded with simple ptfs, thus enabling to quantify how much prediction bias and precision can be gained when increasing the complexity of ptfs and consequently the number and quality of predictors required.

Fig. 1 :

 1 Fig. 1: Triangle of texture used (a), texture of the horizons used to develop the class-and continuous-ptfs (b) and texture of those used to test their validity (c).

Fig. 1 :Fig. 2 :

 12 Fig. 1 : Triangle de texture utilisé (a), texture des horizons utilisés pour développer les classes de fpt et les fpt continues (b) et texture des horizons utilisés pour discuter leur validité (c).

Fig. 2 :

 2 Fig. 2 : Validité des classes de fpt texturales (a), texturo-structurales (b) et VG texturales (c), ainsi que des fpt continues (d) et VG continues.

θ θ θ θ s = 1 .

 1 1658 -0.0032*C -0.4737*D + 2*10 -7 *S 2 -0.0001*OC 2 + 0.0373*C -1 + 0.0131*S -1 -0.0072*ln(S) + 0.00003*OC*C + 0.0022*D*C -0.0002*D*OC -0.0001*S (R 2 = 0.95) α α α α * = 25.61+ 0.0439*C + 0.1129*S + 1.1914*OC + 32.21*D -10.48*D 2 -0.0009*C 2 -0.0146*OC 2 -0.3781*OC -1 -0.0178*ln(S) -0.1032*ln(OC) -0.1*D*S -0.6001*D*OC (R 2 = 0.26) n * = -15.29 -0.0659*C + 0.0115*S -0.2115*OC + 12.33*D -1.3578*D 2 + 0.0006*C 2 + 0.0031*OC 2 + 4.0005*D -1 + 2.2003*S -1 + 0.1643*OC -1 -0.1205*ln(S) + 0.2693*ln(OC) -9.9367*ln(D) + 0.003*D*C + 0.0694*D*OC (R 2 = 0.35) θs is a model parameter, α * , n * are transformed model parameters in the Mualem-van Genuchten equations; C = percentage clay (i.e., percentage < 2 µm); S = percentage silt (i.e., percentage between 2 µm and 50 µm); OC = organic carbon g.kg -1 ; D = bulk density.

Table 1

 1 Characteristics of the horizons of the data set used to develop the ptfs and of the test data set. Tableau 1 Caractéristiques des horizons de l'ensemble de données utilisé pour développer les fpt et de celui utilisé pour en discuter la validité.

	Particle size
	distribution (%)

Table 3

 3

	Texturo-structural class-ptfs developed.
	Tableau 3
	Classes de fpt texturo-structurales développées.
					Volumetric water content (cm 3 cm -3 )
			θ1.0	θ1.5	θ2.0	θ2.5	θ3.0	θ3.5	θ4.2
	Very Fine	1.10≤ Db<1.30	0.498	0.473	0.451	0.423	0.405	0.371	0.330
	(n =15)	1.30≤ Db<1.50	0.459	0.439	0.428	0.405	0.385	0.352	0.328
		1.50≤ Db<1.70	0.359	0.359	0.361	0.353	0.347	0.340	0.294
	Fine	1.00≤ Db<1.20	0.519	0.499	0.494	0.461	0.431	0.373	0.281
	(n = 32)	1.20≤ Db<1.40	0.452	0.443	0.421	0.385	0.373	0.340	0.271
		1.40≤ Db<1.60	0.391	0.378	0.361	0.344	0.321	0.289	0.250
		1.60≤ Db<1.80	0.338	0.334	0.325	0.307	0.291	0.275	0.244
	Medium Fine	1.20≤ Db<1.40	0.348	0.338	0.323	0.291	0.232	0.188	0.153
	(n = 96)	1.40≤ Db<1.60	0.359	0.343	0.328	0.298	0.258	0.211	0.175
		1.60≤ Db<1.80	0.353	0.345	0.329	0.303	0.263	0.230	0.190
	Medium	1.20≤ Db<1.40	0.354	0.337	0.314	0.278	0.245	0.193	0.140
	(n = 117)	1.40≤ Db<1.60	0.346	0.329	0.310	0.275	0.235	0.193	0.146
		1.60≤ Db<1.80	0.320	0.307	0.293	0.270	0.248	0.214	0.167
		1.80≤ Db<2.00	0.296	0.289	0.274	0.266	0.258	0.231	0.186
	Coarse	1.40≤ Db<1.60	0.241	0.210	0.164	0.135	0.106	0.093	0.075
	(n = 32)	1.60≤ Db<1.80	0.253	0.231	0.188	0.156	0.126	0.103	0.077

Table 4

 4 Parameters of the van Genuchten's model corresponding to the VG textural class-ptfs developed according to the type of horizon (topsoil and subsoil). Tableau 4 Paramètres du modèle de van Genuchten correspondant aux classes de ptf VG texturales développées en fonction du type d'horizon (horizon de surface et horizon de subsurface).

		θr	θs	α	n	m
	Topsoils
	Coarse	0,025	0,397	1,0592	1,1530	0,1327
	Medium	0,010	0,428	0,4467	1,1000	0,0909
	Medium fine	0,010	0,465	0,6860	1,1027	0,0931
	Fine	0,010	0,477	0,6153	1,0652	0,0612
	Very Fine	0,010	0,587	5,9433	1,0658	0,0617
	Subsoils
	Coarse	0,025	0,367	1,0535	1,1878	0,1581
	Medium	0,010	0,388	0,1851	1,0992	0,0903
	Medium fine	0,010	0,416	0,1611	1,0978	0,0891
	Fine	0,010	0,437	0,1334	1,0632	0,0594
	Very Fine	0,010	0,472	0,0745	1,0499	0,0475

Table 5

 5

	Regression coefficients and coefficient of determination R 2 recorded for the
	continuous-ptfs developed.
	Tableau 5
	Coefficients de régression et coefficients de détermination R 2 enregistrés
	pour les ptf continues développées.
				Water potential (hPa)
			-33	-100	-330	-1000	-3300	-15000
	a	0.4701 ***	0.3556 ***	0.2620 ***	0.1301 ***	0.0184	-0.0504	-0.0786 **
	b	0.0026 ***	0.0029 ***	0.0034 ***	0.0038 ***	0.0045 ***	0.0047 ***	0.0045 ***
	c	0.0006 ***	0.0008 ***	0.0012 ***	0.0012 ***	0.0008 ***	0.0005 ***	0.0003 ***
	d	-0.0006	-0.0002	0.0002	0.0010	0.0017 ***	0.0012 **	0.0004
	e	-0.1447 ***	-0.0939 ***	-0.0647 ***	-0.0084	0.0398 *	0.0697 ***	0.0710 ***
	R 2	0.59	0.64	0.69	0.74	0.77	0.82	0.86

θ = a + (b×%Cl) + (c×%Si) + (d×%OC) + (e×Db) with θ volumetric water content at a given water content. *** P = 0.001. ** P = 0.01. * P = 0.05.

Table 6

 6

	VG continuous-ptfs developed for the parameters of the van Genuchten's model.
	Tableau 6
	Relations correspondent aux fpt VG continues développées pour les paramètres du modèle de
	van Genuchten.

Table 7

 7 Validity of the continuous-and class-ptfs according to the water potential. Tableau 7 Validité des classes de fpt et des fpt continues aux différentes valeurs de potentiel de l'eau.

							Volumetric water content (cm 3 .cm -3 )
				Mean Error of Prediction (MEP')				Standard Deviation of Prediction (SDP')
		θ1.0	θ1.5	θ2.0	θ2.5	θ3.0	θ3.5	θ4.2	θ1.0	θ1.5	θ2.0	θ2.5	θ3.0	θ3.5	θ4.2
	Textural class-ptfs	-0.006	0.004	0.003	0.001	-0.004	-0.001	-0.020	0.046	0.046	0.044	0.045	0.047	0.044	0.042
	Texturo-structural class-ptfs	-0.006	0.002	0.002	0.001	-0.005	-0.002	-0.019	0.042	0.042	0.041	0.043	0.045	0.044	0.041
	VG class-ptfs	0.014	0.007	-0.003	-0.008 -0.007	0.007	0.002	0.045	0.045	0.045	0.046	0.046	0.043	0.040
	Continuous-ptfs	-0.006	0.001	0.005	0.001	-0.003	0.002	-0.022	0.044	0.044	0.040	0.039	0.036	0.032	0.030
	VG continuous-ptfs	0.012	0.004	-0.008	-0.017 -0.020	-0.008	-0.016	0.044	0.041	0.038	0.039	0.035	0.033	0.032


Marwen Moussa
email: marwen.moussa@grignon.inra.fr

Violaine Athes

Yohann Imbert

Isabelle Souchon

PERVAPORATION WITH COMPOSITE PVA MEMBRANES FOR THE DEHYDRATION OF BIOETHANOL: EFFECT OF VOLATILE ORGANIC IMPURITIES ON PERMEATION PROPERTIES

Introduction

Reducing dependency on fossil fuels is a major economical and environmental challenge that stimulated the development of renewable energy sources such as bioethanol. At present, bioethanol fuel is used in several countries, in the form of its derivative ETBE (Ethyl Tertiary Butyl Ether) or blended with gasoline at a rate of 5% to 100% v/v. Bioethanol needs to be dehydrated prior to its use as a fuel. According to EU directive 15376, the residual amount of water in bioethanol must not exceed 0.3% w/w. At present, the traditional techniques used for ethanol dehydration in the world industry include azeotropic distillation and dehydration on molecular sieves. Pervaporation is a membrane process, largely described as a promising alternative to the traditional techniques of ethanol dehydration [START_REF] He | Recent advances in membrane technologies for biorefining and bioenergy production[END_REF][START_REF] Kaminski | Renewable energy source-Dehydrated ethanol[END_REF]. Indeed, pervaporation is considered as more flexible, cleaner and requiring less energy than these techniques. Numerous works have been carried out in order to study the performance of hydrophilic pervaporation [START_REF] He | Recent advances in membrane technologies for biorefining and bioenergy production[END_REF][START_REF] Namboodiri | High permeability membranes for the dehydration of low water content ethanol by pervaporation[END_REF][START_REF] Bolto | A review of membrane selection for the dehydration of aqueous ethanol by pervaporation[END_REF]. Most of them described studies performed using rectified ethanol (from fermented sugar cane or beet and starch) that has undergone several distillations to remove impurities. Ethanol obtained from agricultural residues and lignocellulosic biomass contains high amount of impurities, mainly volatile organic compounds (VOCs). The removal of VOCs by dedicated rectification increases the size and the energy consumption of the whole process. For example, the fermentation of grape marc produces bioethanol that contains up to 30000 ppm of methanol and some aldehydes and esters in smaller quantities. These VOCs can alter the performance of membrane processes used for ethanol dehydration. This work was aimed to study the performance of commercial composite PVA membranes in dehydrating bioethanol, with a special focus on the effect of methanol, selected as a first model VOC, on permeation properties.

Materials and Methods

Pervaporation experiments

Pervaporation experiments were conducted using a laboratory-scale unit. The feed was placed in the heated vessel and recirculated using a volumetric pump. The recirculation flowrate was set at 100 kg.h -1 . The temperature was set at 60°C. The vacuum was applied on the shell side at 3 mbar. The unit was equipped with several digital sensors to monitor pressure, temperature, and flowrate. PERVAP 1211 PVA (Polyvinyl alcohol) composite membranes were used (2-5 µm of active layer thickness, surface area of 170 cm²). Three different flat membranes (M1, M2 and M3) were tested. The permeate side was connected to a vacuum line and the permeate stream was condensed into two parallel cold traps maintained at -80°C. Permeate samples were then collected and weighted out. For each experiment, 10 kg of azeotropic bioethanol was used. Methanol (2% w/w) was added for some experiments. Fluxes and selectivity were calculated as following:

where J is the total permeate flux, m the mass of the permeate, A the membrane surface area and t the permeation time. yi and yj are respectively the weight fractions of component i and j in the permeate. xi and xj are respectively the weight fractions of component i and j in the feed. Partial fluxes were calculated using the total flux and the weight fraction of each component in the permeate. For a known partial flux, the apparent transfer coefficient K app was obtained after determining the driving force ( ∆ p i =p i,f -p i,p ) where p i,f is the partial pressure of component i in the feed (calculated using the Raoult's law) and p i,p is the partial pressure of component i in the permeate (calculated using the Dalton's law). Di and Si are the diffusivity and the sorption coefficient of the component i into the membrane. z is the membrane thickness under pervaporation conditions. Analysis Water concentration in feed and retentate samples was determined using Karl Fischer titration (756 KF Coulometer). Ethanol concentration in permeate samples was determined by HPLC analysis on a

At m J = ) , , ( ) , , ( p i p f i p Kapp p i p f i p z i S i D i J - = - = xj yj xi yi j i / / , =
α P680 HPLC Pump DIONEX equipment using an ion exchange column (300 mm x 7.8 mm) with H 2 SO 4 0.01 N as the mobile phase and propionic acid as the internal standard. The apparatus is coupled to a refractometer detector (410 Diff. Refract, Waters). Methanol concentration was measured by gas chromatography through a direct injection in a CPG Agilent 6890 equipped with a split injector at 200°C, an auto sampler (Combipal, Varian), a flame ionization detector (220°C; H 2 : 40 mL/min; air: 450 mL/min; makeup gas He: 33 mL/min) and a CP Wax 57-CB column (50 m x 0,25 mm x 0,2 µm; Agilent).

Results and Discussion

Table 1. Pervaporation of ethanol-water mixture (94% w/w of ethanol in the feed) at 60°C and 3 mbar.

The calculation of driving force and transfer coefficient makes it possible to evaluate the contribution of each of them on the partial flows. Table 1 shows that the partial flow for ethanol is mainly determined by the driving force. This high magnitude of driving force comes from the high partial pressure of ethanol if the feed mixture. Water permeation occurs with a significantly higher flux with regard to ethanol thanks to its high transfer coefficient. Comparison with literature results is not always straightforward due to differences in experimental conditions and in membrane properties such as crosslink density and nature. Nevertheless, even with some differences between the three membranes tested in this work (Table 1), it can be noticed that the membrane selectivity is near of that reported for PVA membranes [START_REF] Namboodiri | High permeability membranes for the dehydration of low water content ethanol by pervaporation[END_REF][START_REF] Bolto | A review of membrane selection for the dehydration of aqueous ethanol by pervaporation[END_REF]. Table 2. Pervaporation of ethanol-water-methanol mixture (94% w/w of ethanol and 2% w/w methanol in the feed) at 60°C and 3 mbar.

Table 2 shows that the permeation fluxes were increased after adding 2% w/w methanol to the feed. The increase in ethanol flux was more noticeable (60% for M2) than that observed for water (20%). The resulting selectivity for water was then decreased with regard to Table1. These results are directly related to the increase in transfer coefficient of both water and ethanol when methanol is added. Methanol molecules did not seem to induce any competition effect with regard to water and ethanol molecules. Because of its low diffusive cross-section and hydrophobicity (data not shown), methanol would be considered to have better sorption and diffusion than ethanol, as reported in literature for binary alcohol-water mixtures [START_REF] Burshe | Sorption and permeation of binary water-alcohol systems through PVA membranes crosslinked with multifunctional crosslinking agents[END_REF]. In this work, the transfer coefficient for methanol was lower than that obtained for ethanol and water. The resulting selectivity for methanol with regard to ethanol was near 1 (data not shown). Moreover, the low values of methanol flux exclude the hypothesis of coupling effect with water and ethanol permeation. It is then suggested that methanol molecules would be plasticized inside the membrane, inducing modification of membrane structure and swelling degree in a way that increases the permeability (D i xS i ) to water and ethanol.

Conclusions

This work highlights the effects of methanol, considered as a first example of VOCs, on water and ethanol transfer in PVA hydrophilic membranes. These results have not yet been reported previously.

Possible mechanisms involve modifications of the membrane structure and permeability. Further work is needed to better understand these mechanisms, by using other VOCs with selected properties and by modeling the membrane molecular dynamics.


Othmane Nait Hamoud

Tayeb Kenaza

Yacine Challal

Diffie Hellman

Security in Device-to-Device communications (D2D): a survey

Keywords: Resisted Attacks Imple, Simul, In Cover, Relay EPC Involve Same operator -Different operator IBE-ECC ECDH Traffic offload -Social network -

Device-to-Device (D2D) communication is a promising technology for the next generation mobile communication networks (5G). Indeed, it is expected to allow high throughput, reduce communication delays and reduce energy consumption and traffic load. D2D technology will enhance the capacity and the performance of traditional cellular networks. Security issues must be considered in all type of communication, especially when it comes to wireless communication. In this paper, we propose taxonomy based on the review of recent works which have addressed the security issues in D2D communications. I.

INTRODUCTION

The rapid growth in the number of mobile internet subscribers has fostered the emergence of various new applications and services. This implies an exponential growth of mobile data traffic. Consequently, a huge burden is imposed for the cellular infrastructure in terms of spectrum utilization, overall throughput, communications delays and energy consumption.

Expecting to be one of the technology components of the evolving 5G architecture, Device-to-Device (D2D) communications is promising solution to offload the cellular infrastructure from the traffic encumbrance. Indeed, D2D communications approach allows device users (device such Smartphone, tablet, etc.) to establish direct communication links with each other without passing through an access point or a core network of a cellular infrastructure. The main difference between the expected 5G and the first four generations is that 5G is heading towards device-centric network architecture contrary to the previous generations which have been network centric. In 5G, device user is expected to actively perform operations which were earlier being performed by the network such as storage, relaying and content delivery [START_REF] Gandotra | A survey on device-to-device (D2D) communication: architecture and security issues[END_REF]. Academicians, industrials, and standard institutions have paid considerable attention for D2D communications technology. In academia, different surveys have been proposed in the literature [START_REF] Asadi | A survey on Device-to-Device communication in cellular networks[END_REF][START_REF] Liu | Device-to-Device communication in LTE-Advanced networks: A survey[END_REF][START_REF] Gandotra | A survey on device-to-device (D2D) communication: architecture and security issues[END_REF] in which, different fields related to this technology was addressed (node discovery, interference and radio resource management, use cases and requirements, power control, system architecture and design, etc.).

In industry, Qualcomm has developed FlashLinQ [START_REF] Wu | FlashLinQ: A synchronous distributed scheduler for peer-to-peer ad hoc networks[END_REF] to implement for the first time D2D communication as subsystem underlying cellular networks to enable direct communications among proximity devices in different scenarios (content sharing, gaming, social networking, etc.). FlashLinQ was designed to work in licensed cellular band based on Time Division Duplexing-Orthogonal Frequency Division Multiple Access technology (TDD-OFDMA) which is the same as LTE-A system, allowing devices to discover neighbors in a large range with high efficiency.

The work of standardizing this new paradigm is underway by the Third Generation Partnership Project (3GPP) under the proposal Proximity Services (ProSe) [START_REF]3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Feasibility study for Proximity Services (ProSe) (Rel 12)[END_REF] which allows enabling direct communication between proximate devices. ProSe combines two types of services, proximity discovery and direct communication. In [START_REF] Lin | An overview of 3GPP device-to-device proximity services[END_REF], a brief overview of standardization activities of the 3GPP ProSe in LTE-A is presented.

Security issues must be considered in all type of communication, especially when it comes to wireless communication. Despite a very rare works, security in D2D communication is not seriously and well handled in the literature. D2D communications face many security challenges when it will applied to the future 5G systems.

II. OVERVIEW OF D2D COMMUNICATIONS

Initially, direct communications were introduced in the third generation networks (3G) within the wireless personal network (WPAN) and wireless local area network (WLAN) technologies. These technologies occurred on unlicensed band which didn't provide Quality of Service (QoS) guarantees due to the uncontrollable interference. In spite of the role which can play D2D paradigm to enhance performance of cellular networks, cellular operators did not pay attention to D2D communications because of the limited benefits of local communications services. However, with the growth of traffic due especially to the increasingly popularity of mobile applications based on devices' proximity such as social networking, network gaming, etc., cellular operators are getting attracted towards the D2D technology until its introduction in the fourth generation (4G) through LTE-Direct and FlashLinQ [START_REF] Wu | FlashLinQ: A synchronous distributed scheduler for peer-to-peer ad hoc networks[END_REF].

A. Scenarios and use cases

Different scenarios and use cases were proposed by 3GPP in [START_REF]Feasibility study for proximity services (ProSe)[END_REF]. Depending on the degree of implication of a Cellular Network Operator (CNO) in D2D communications, three typical scenarios and use cases are shown in Figure 1.

Figure1. Typical scenarios and use-cases in D2D

communications.

1. In coverage scenario where the control link is totally ensured by the CNO. The main use case in this scenario is traffic offloading. For example, if the same content is requested by different UEs from the same eNB (video streaming of football match), this later will transmit the content to UEs as cluster heads, which in turn multicast the content through D2D links to the rest of UEs belonging to the corresponding cluster. Local Social Networks (NextDoor, Topix, Foursquare, etc.) are emerging in nowadays and allow companies to target clients in a specific geographic location with multiple and attractive services (advertising). Through D2D links, such type of networks can be more efficient.

2. Partial coverage scenario where the control link is partially ensured by the CNO. The main use case in such a scenario is the extension of cellular network coverage in areas (refugee camp, rural areas, etc.) where the cost of traditional infrastructure had previously made the facilities impossible to justify.

3. Out of coverage scenario where the control link is ensured by the devices themselves. The typical use case in this scenario is the emergence and critical public safety communications where the cellular infrastructure is absent due to natural disaster, terrorism attacks, etc.

In the literature, different works have investigated potential D2D use cases such as traffic offloading [START_REF] Sedidi | Key Exchange Protocols for Secure Deviceto-Device (D2D) Communication in 5G[END_REF][START_REF] Orsino | Validation information security framework for offloading from LTE onto D2D links[END_REF], social networking [START_REF] Sedidi | Key Exchange Protocols for Secure Deviceto-Device (D2D) Communication in 5G[END_REF][START_REF] Zhang | Social Network Aware Device-to-Device Communication in Wireless Networks[END_REF][START_REF] Chen | Exploiting Social Ties for Cooperative D2D Communications: A Mobile Social Networking Case[END_REF], smart media sharing [START_REF] Ramasubramanian | Secure and smart media sharing based on a novel mobile Device-to-Device communication framework with security and procedures[END_REF][START_REF] Zhang | SeDS: Secure data sharing strategy for D2D communication in LTE-Advanced networks[END_REF][START_REF] Zhang | Social Network Aware Device-to-Device Communication in Wireless Networks[END_REF], intermittent cellular connectivity [START_REF] Ometov | Securing Network-Assisted Direct Communication: The Case of Unreliable Cellular Connectivity[END_REF][START_REF] Ometov | Implementing Secure Network-Assisted D2D Framework in Live 3GPP LTE Deployment[END_REF][START_REF] Orsino | Validation information security framework for offloading from LTE onto D2D links[END_REF], extended coverage [START_REF]3rd Generation Partnership Project; Technical Specification Group Services and System Aspects; Feasibility study for Proximity Services (ProSe) (Rel 12)[END_REF][START_REF] Panaousis | Secure message delivery games for Device-to-Device communications[END_REF][START_REF] Li | Game-Theoretic analysis of Cooperation incentive strategies in mobile Ad Hoc networks[END_REF], disaster rescue [START_REF] Alam | Secure device-to-device communication in LTE-A[END_REF].

B. System architecture

Before presenting the system architecture of the D2D communications, we present the basic architecture of the core network of 3GPP's LTE wireless communication standard, the Evolved Packet System (EPS). The main component of the EPS is the Evolved Packet Core (EPC). Figure 2 illustrates a basic architecture of the EPS in which, a UE is connected to the EPC over a Radio Access Network technology (RAN). In order to make the scaling independent, it was decided to separate in the EPC the user plane (data) and the control plane (signaling).

3GPP has proposed D2D communication (ProSe) as an underlay network of existing LTE-A networks [START_REF]Study on architecture enhancements to support proximity services (ProSe) (Release 12)[END_REF]. They integrated two new entities: (1) ProSe function which may provide connections between application servers and UEs and handle ProSe related functions (UE registration, UEs discovery, security, etc.) and (2) ProSe application server which serves UEs requesting ProSe services through a logical link. Figure 3 shows simplified network architecture for the ProSe, where the control plane can be ensured in three different levels: UE, RAN and EPC.

In the EPS of the 3GPP, ProSe features consists of [START_REF]Proximity-Based services (ProSe) Stage 2 (Release 14)[END_REF]:

(1) ProSe Discovery (ProSe-D), which identifies that ProSeenabled UEs are in proximity using E-UTRA technology (with or without E-UTRAN) or EPC; and (2) ProSe Direct communication (ProSe-DC), which enables establishment of communication paths (using E-UTRAN or WLAN) between two or more ProSe-enabled UEs that are in direct communication range. In the context of Public Safety usage, UEs can establish the communication path directly, regardless of whether they are served by E-UTRAN; and ProSe-DC is facilitated by the use of a ProSe UE-to-Network Relay, acting as a relay between E-UTRAN and UEs. C. Classification D2D communications may be the bridge between ad hoc networks and centralized networks. On one hand, they may integrate into their ad-hoc aspect other promising techniques such as cooperative communication [START_REF] Li | Game-Theoretic analysis of Cooperation incentive strategies in mobile Ad Hoc networks[END_REF][START_REF] Chen | Stimulating cooperation in vehicular ad hoc networks: a coalitional game theoretic approach[END_REF][START_REF] Sun | SYNERGY: A game-theoretical approach for cooperative key generation in wireless networks[END_REF][START_REF] Chen | Exploiting Social Ties for Cooperative D2D Communications: A Mobile Social Networking Case[END_REF] and cognitive radio [START_REF] Sakr | Cognitive and energy harvesting-based D2D communication in cellular networks: Stochastic geometry modeling and analysis[END_REF][START_REF] Liu | Device-to-device communication in LTEadvanced networks: a survey[END_REF] in order to enhance spectrum efficiency. On another hand, the centralized aspect of cellular networks may resolve interference issues.

The D2D communication can occur either on operator's licensed spectrum (underlying LTE-A networks) or unlicensed spectrum (Bluetooth, WiFi-Direct). Authors in [START_REF] Asadi | A survey on Device-to-Device communication in cellular networks[END_REF] proposed taxonomy based on the D2D communication spectrum and reviewed the available literature under the proposed taxonomy.

In the licensed band, D2D communications cohabit with cellular ones and gain advantages in terms of spectral efficiency and interference control and management. In this category, D2D links are further divided into underlay and overlay subcategories, where D2D and cellular links share the same radio resources in the first subcategory, and are given dedicated radio resources in the second one. The main advantage in underlay D2D communications is the spectral efficiency. However, power control and resource allocation solutions have to be more complex; and a user cannot perform simultaneously cellular and D2D communications. In contrast, overlay D2D eliminates the interference issue between cellular and D2D communications, but it wastes radio resources.

In the unlicensed band, there is no interference between cellular and D2D communications, but an extra interface which uses other wireless technologies (WiFi-Direct, Bluetooth, etc.) is required. D2D communications in this category are further divided into subcategories: controlled and autonomous communication. In controlled unlicensed D2D communication, the cellular operator controls both cellular and wireless technology interfaces. In contrast, the device user controls the D2D communication interface in autonomous unlicensed D2D communication. Simultaneous cellular and D2D communications can be made by a device user in this category.

In the following we propose a revised classification which highlights the hybridization and flexibility of D2D communication techniques, compared to available other techniques. The classification we proposed (Fig 4) is more practical to understand existing solutions and to apprehend new ones related to D2D communication since it is based on the proximity services (discovery or direct communication), on the spectrum (in band or out band) and on the involvement level of the cellular infrastructure (assisted, controlled or autonomous). The assistance of cellular infrastructure refers to controlling D2D communication links at the RAN level (i.e. eNB).

Nowadays, mobile devices support simultaneously multiple radio access technologies (2G, 3G, 4G, WiFi-Direct, Bluetooth, NFC, etc.), and are given more and more processing and storage capacity. Besides, with the variety of radio access technologies, multiple formats of cells (micro, pico and femto cells) with different power levels are deployed in the same geographical area. Thus, D2D communication can benefit on one hand from this diversity from the point of view of signal control, energy efficiency, resource allocation, throughput, and new services and applications, and on another hand, from the point of view of context and scenario in which they are applied.

Through this classification, we can imagine a brunch of solutions, depending on the context and the situation in which, D2D communication will be utilize. For example, in order to offload cellular traffic through D2D links, DataSpotting [START_REF] Bao | DataSpotting: Exploiting Naturally Clustered Mobile Devices to Offload Cellular Traffic[END_REF] adopted a hybrid mode of spectrum allocation (in band and out band). The system uses licensed band to control channel for all the setup procedures until activating both the content requester and provider into WiFi ad-hoc mode. Cellular operator assists UE only in neighborhood discovery. Under the assistance of an eNB, FlashLinQ works over dedicated licensed band to enable UEs to discover proximity devices in a large range with high efficiency and to communicate directly in a distributed and autonomous manner over the licensed band. Relay-By-Smartphone is a multi-hop D2D communication system which was developed for disaster relief application [START_REF] Nishiyama | Relay-by-Smartphone: Realizing Multihop Device-to-Device Communications[END_REF]. According to the situation (neighbor node density, mobility pattern, remaining battery power, etc.), a smartphone could switch between MANT operation mode and DTN operation mode in the message delivery process in such a way that the overall message delivery performance is improved. In a centralized system, network performance is guaranteed due to resource control and interference coordination provided by the operator. However, the system will cost larger overhead and will result in a limitation of privacy and scalability. By comparison, in a distributed system, EUs are autonomous entities, each with its own objective, and its own actions, independently and in a self-directed manner. The system will therefore be more flexible, autonomous and scalable.

III. SECURITY IN D2D COMMUNICATIONS

This section treats security threats and requirements in D2D communications.

A. Security threats

The radio nature of D2D communications introduces various security threats [START_REF] Zhang | SeDS: Secure data sharing strategy for D2D communication in LTE-Advanced networks[END_REF] [START_REF] Zhang | Security-aware Device-to-Device Communications Underlaying Cellular Networks[END_REF]. The main threats are:

 Eavesdropping attack: an attacker passively listens to the radio channel between UE devices in order to get sensitive data. Data confidentiality in the cryptography approach can parry this threat.  Impersonate attack: an attacker can pretend to be a legitimate UE device or eNB to get access to the traffic data. Authentication in the cryptography approach can parry this threat.  Forge attack: an attacker may forge the content and send the fake data to the rest of UEs, which prejudices the system. Data integrity (digital signature) in the cryptography approach can parry this threat.  Free-riding attack: in order to reduce system availability in D2D communications, an attacker may encourage selfish behavior of some UEs to preserve energy consumption so they may not be willing to send contents to others while receiving its demanding data from their peers. Such vulnerability may affect Quality of Experience (QoE) thus irritates user experiences and hinders the adoption of D2D communications. To resist such an attack, it is necessary to develop a cooperation stimulation mechanism [START_REF] Li | Game-Theoretic analysis of Cooperation incentive strategies in mobile Ad Hoc networks[END_REF][START_REF] Chen | Stimulating cooperation in vehicular ad hoc networks: a coalitional game theoretic approach[END_REF][START_REF] Sun | SYNERGY: A game-theoretical approach for cooperative key generation in wireless networks[END_REF][START_REF] Chen | Exploiting Social Ties for Cooperative D2D Communications: A Mobile Social Networking Case[END_REF][START_REF] Jiang | Secure beamforming in cooperative D2D communications with simultaneous wireless information and power transfer[END_REF]].  Active attack on control data: an attacker tries to change the control data.

Authentication, confidentiality and integrity in the cryptography approach can parry this threat.  Privacy violation: some privacy-sensitive data such as identity, location, etc. are more concerned by D2D services functionalities, so this personal information must be concealed to non-authorized parties.  Denial-of-Service (DoS) attack: it consists of rendering up unavailable a service in D2D communications. In [START_REF] Hadiks | A study of stealthy denial-ofservice attacks in Wi-Fi direct device-to-device networks[END_REF], authors has shown via experimental study about exploration on characteristics of DoS attacks on Android devices in D2D underlaying network environment that malicious devices can stealthily impair or even totally block the connection of legitimate devices in the underlaying network.

B. Security requirements

Due to the aforementioned threats, a secure D2D communications system should fulfill the following security requirements [START_REF] Haus | Security and privacy in Device-to-Device (D2D) communication: a review[END_REF] [33] [START_REF] Zhang | Security-aware Device-to-Device Communications Underlaying Cellular Networks[END_REF], whether they are assisted, controlled or autonomous:

 Authentication: identification of communicating parties must to be checked.  Data confidentiality: transmitted data between devices must be secret using encryption mechanisms.  Data integrity: data transferred by authorized devices should be verified that they are not altered.  Privacy: privacy information such identity, SIM card number, geographical position, etc. must be preserved.  Traceability: it is necessary to be able to identify the source identity of false messages. In [START_REF] Abd-Elrahman | Fast Group Discovery and Non-Repudiation in D2D Communications using IBE[END_REF], authors consider the given conflicting goals between privacy and traceability.  Anonymity: communicating UEs may be anonymous to each other and from an adversary.  Non-repudiation: refers to the ability to prevent UEs from denying transmission or reception of a message.

In cryptography approach, digital signature is an efficient tool to prevent from transmission nonrepudiation, while additional mechanism is required to ensure reception non-repudiation.  Availability: D2D services should be accessible anytime and anywhere even under DoS or free-riding attacks, lest users be discouraged to use this technology.  Revocability: refers to ability to reprieve user privilege of a D2D service if it is detected as malicious.  Fine-grained Access Control (FAC): takes into account small granularity of an access rule specified to a UE when accessing in its service. It's seen as an effective solution to overcome privacy and data transmission security issues.

IV. TAXONOMY ON D2D SECURITY SOLUTIONS

A general approach to address security issues in D2D communications can be based on network layers on which security is concerned. From this point of view, a complete security solution can be designed to provide a complete protection for the devices involved in D2D communications. Such a solution must be based on security protocols built on each layer which will be called upon to cooperate together. Besides, this approach can enable an agile defensive response for a system under attack by shifting D2D communication to a new combination of encryption implementation, routing protocol, and media access technique and frequency band [START_REF] Abualhaol | Securing D2D Wireless Links by Continuous Authenticity with Legitimacy Patterns[END_REF].

This layer based approach of security can provide a clear understanding of D2D communications security and help towards better protocol design. Based on this approach, we provide in this section an extended taxonomy of security solutions depending on which layer a solution belongs. Recently, Abd-Elrahman et al. [START_REF] Abd-Elrahman | Fast Group Discovery and Non-Repudiation in D2D Communications using IBE[END_REF] proposed a solution based on the Identity-Based Encryption (IBE) and Elliptic Curve Cryptography (ECC) mechanisms for key generation to secure the exchanged messages during the discovery and communication phases. The proposed solution is discussed under two D2D use cases (same operator and different operators) and is further used to introduce an efficient key management system for group communication. Besides, authors designed a protocol based on the modified IBE system to ensure privacy support and legal interception for D2D clients. For this aim, authors have validated this protocol in a platform for a social network scenario using D2D aspect in same and different operators' use cases. Authors proposed also in [START_REF] Abd-Elrahman | D2D Group Communications Security[END_REF] a Group Key Management (GKM) mechanism for the same purpose as in [START_REF] Abd-Elrahman | Fast Group Discovery and Non-Repudiation in D2D Communications using IBE[END_REF]. In this work, they used multiple Private Key Generators (PKGs) which is more suitable for different operators' use case than a single one as proposed in [START_REF] Abd-Elrahman | Fast Group Discovery and Non-Repudiation in D2D Communications using IBE[END_REF].

In [START_REF] Sedidi | Key Exchange Protocols for Secure Deviceto-Device (D2D) Communication in 5G[END_REF], three key exchange protocols for secure network assisted D2D communication in a cellular network are proposed. These protocols are based on the standard Diffie-Hellman based key exchange, but they differ in the role of eNB in the authentication process. Authors have considered traffic offload and social networking use cases.

Zhang et al. have proposed a secure data sharing protocol (SeDS) for D2D communications in LTE-A network based on symmetric and asymmetric encryption [START_REF] Zhang | SeDS: Secure data sharing strategy for D2D communication in LTE-Advanced networks[END_REF]. Authors consider media sharing scenario for the ease of the understanding which can be extended to be more general ones. The involvement of EPC is assured by a gateway which serves as the gate from the local subsystem to the core network. In order to completely offload the cellular network, authors proposed an interesting idea in [START_REF] Zhang | Security-aware Device-to-Device Communications Underlaying Cellular Networks[END_REF] but which has not been investigated yet. The idea introduces Certificate Less Public Key Cryptography (CL-PKC) [START_REF] Al-Riyami | Certificateless public key cryptography[END_REF] to secure D2D communications.

In order to enable two UEs to establish a secret key to secure D2D communications without prior knowledge or involvement of EPC, Shen et al. proposed in [START_REF] Shen | Secure key establishment for Device-to-Device communications[END_REF][START_REF] Shen | Secure Device-to-Device communications over WiFi Direct[END_REF] a key agreement protocol based on the Diffie-Hellman (DH) key exchange and a commitment schemes. In [START_REF] Goratti | Connectivity and security in a D2D communication protocol for public safety applications[END_REF], a probabilistic key management scheme was derived from wireless sensor networks (WSN) and employed to secure D2D communications for a public safety scenario. In [START_REF] Kwon | Secure authentication using ciphertext policy attribute-based encryption in mobile multi-hop networks[END_REF], a novel authentication protocol is proposed in a non network assisted mode with a secure initial key establishment using cipher-policy attribute-based encryption (CP-ABE). This protocol allows the communicating parties to mutually authenticate and derive the link key in a secure manner in a multi hop scenario.

Alam et al. in [START_REF] Alam | Secure device-to-device communication in LTE-A[END_REF] have reused existing security solutions of LTE-A technology in order to secure D2D communication for three types of scenario: network offloading, social networking and disaster rescue. The proposed mechanisms are based on the involvement of a cellular network as a trustworthy third party and the presence of a user application. An authentication system for D2D communication under LTE is proposed by Wang et al. [START_REF] Wang | Authentication system for device-to-device communication and authentication method therefore[END_REF], in which a shared master key is sent by the core network to UEs in order to derive a session key.

Besides, since social networking is considered as the main scenario for D2D communications, security and privacy in mobile social network is a challenging work to construct social trust and social ties promoting efficient cooperation with privacy preservation among users. Many works have focused on security aspect of social networking [START_REF] Ometov | Securing Network-Assisted Direct Communication: The Case of Unreliable Cellular Connectivity[END_REF][START_REF] Ometov | A Novel Security-Centric Framework for D2D Connectivity Based on Spatial and Social Proximity[END_REF][START_REF] Ometov | Implementing Secure Network-Assisted D2D Framework in Live 3GPP LTE Deployment[END_REF][START_REF] Zhang | Social Network Aware Device-to-Device Communication in Wireless Networks[END_REF][START_REF] Chen | Exploiting Social Ties for Cooperative D2D Communications: A Mobile Social Networking Case[END_REF]. Ometov et al. proposed in the context of a networkassisted D2D communication two solutions to maintain and extend the secure D2D operation in case of unreliable cellular connectivity [START_REF] Ometov | Securing Network-Assisted Direct Communication: The Case of Unreliable Cellular Connectivity[END_REF][START_REF] Ometov | A Novel Security-Centric Framework for D2D Connectivity Based on Spatial and Social Proximity[END_REF]. In these solutions, authors consider all of the involved devices to be at least equipped with an LTE and WiFi interfaces and have been connected to the cellular network which is assumed to be their trusted authority. In [START_REF] Ometov | Securing Network-Assisted Direct Communication: The Case of Unreliable Cellular Connectivity[END_REF], authors' target scenario consists on the assisted offloading of devices' cellular data flows onto their WiFi-Direct sessions. Cellular links are used by devices only for transferring signaling information and to communicate with the PKI functions and establish a logical group of securelycommutating devices named a coalition. Based on a mathematical model, the algorithm allows adding new users to secure coalition as well as excluding existing ones from it, even in the case of unreliable cellular network. In order to trial this theoretical solution, an implementation of secure networkassisted D2D framework in live 3GPP LTE deployment was proposed in [START_REF] Ometov | Implementing Secure Network-Assisted D2D Framework in Live 3GPP LTE Deployment[END_REF].

In [START_REF] Ometov | A Novel Security-Centric Framework for D2D Connectivity Based on Spatial and Social Proximity[END_REF], authors' target scenario consists on providing additional coverage for users that are facing intermittent cellular connectivity and thus helping disseminate content to larger numbers of device users. Coalition formation (clustering) in this work is based on game theoretical framework where social proximity (relationships among users) and spatial proximity (effect of cellular transmissions) are considered explicitly. Orsino et al. [START_REF] Orsino | Validation information security framework for offloading from LTE onto D2D links[END_REF] adopted a gametheoretic optimization approach to secure throughput optimized communications in D2D-assisted cellular system. Authors in [START_REF] Hadiks | A study of stealthy denial-ofservice attacks in Wi-Fi direct device-to-device networks[END_REF] studied the impacts of Denial of Service (DoS) attacks in a D2D underlaying network. Authors' experiments have shown how attacks can force UE to lose the WiFi connection with the access point without being detected by the AP or the cellular network. The goal of this work was to inspire deeper study and more efforts in this field.

In order to offload cellular traffic without increasing the infrastructure cost, the work in [START_REF] Ramasubramanian | Secure and smart media sharing based on a novel mobile Device-to-Device communication framework with security and procedures[END_REF] considered only the network assisted mode to propose a D2D business model and to implement an application level security framework for devices involved in D2D communications.

B. Network layer

D2D communications can be used in a disaster rescue (earthquake) when network infrastructure becomes absent [START_REF] Zhang | SeDS: Secure data sharing strategy for D2D communication in LTE-Advanced networks[END_REF]. In this scenario, devices can play an important role in relaying D2D communications over public safety network which require secure communications. Moreover, secure multi-hop D2D communications can contribute to anonymity against cellular operators [START_REF] Tata | Secure Network Coding based Data Splitting for Public Safety D2D Communications over LTE Heterogeneous Networks[END_REF][START_REF] Tata | Secure Multipath Routing Algorithm for Device-to-Device Communications for Public Safety over LTE Heterogeneous Networks[END_REF][START_REF] Steri | A Novel Multi-hop Secure LTE-D2D Communication Protocol for IoT Scenarios[END_REF][START_REF] Panaousis | Secure message delivery games for Device-to-Device communications[END_REF][START_REF] Jung | Joint operation of routing control and group key management for 5G ad hoc D2D networks[END_REF] (Table 2).

Tata et al. proposed Secure Network Coding based Data

Splitting and Data Shuffling algorithm to secure routing for public safety D2D communications over LTE Heterogeneous Networks (HetNets) without adding additional control traffic [START_REF] Tata | Secure Network Coding based Data Splitting for Public Safety D2D Communications over LTE Heterogeneous Networks[END_REF]. In order to assure confidentiality in the network, the solution consists of applying the data splitting and shuffling mechanisms for forwarding over a butterfly network symbols rather than whole packets through a network coding path. Authors proposed another approach for secure D2D routing if unable to apply network coding transmissions within LTE small cells [START_REF] Tata | Secure Multipath Routing Algorithm for Device-to-Device Communications for Public Safety over LTE Heterogeneous Networks[END_REF]. The proposed algorithm called Secure Load Balancing Selective AOMD (LBS-AOMDV) is based on a multipath coded information transmissions, data splitting, and data shuffling schemes.

In the context of IoT scenario, the work in [START_REF] Steri | A Novel Multi-hop Secure LTE-D2D Communication Protocol for IoT Scenarios[END_REF] proposed a secure protocol for multi-hop D2D communications where LTE-A UEs aggregate data generated in their surroundings by IoT things and the proposed protocol connects UEs to a cellular base station, which transports the traffic to the Internet. The security feature of this solution is based on the work [START_REF] Goratti | Connectivity and security in a D2D communication protocol for public safety applications[END_REF] where a probabilistic key management scheme is employed. In another context where UEs are out of coverage, Panaousis et al. proposed in [START_REF] Panaousis | Secure message delivery games for Device-to-Device communications[END_REF] Secure Message Delivery protocol to choose the most secure path to deliver a message from a sender to a destination in multi-hop D2D network. For this end, authors used game theory to model the interactions between a D2D network and attacker which aims at sending a malicious message through a D2D network.

A joint operation of routing control and group key management for 5G ad hoc D2D networks is proposed in [START_REF] Jung | Joint operation of routing control and group key management for 5G ad hoc D2D networks[END_REF]. To offload the cellular network from the local traffic, the UE is assumed acting in a way that it cans response to either infrastructure or ad hoc D2D communications requirements. So, authors' idea is based on that the dual operation of infrastructure and ad hoc D2D mode communications in the same UE requires the ad hoc node to rely on the network layer function as small as possible. The proposed protocol controls the ad hoc D2D network and manages the group key in selfmanaged group of ad hoc nodes based on their home IP address wherever they move. The authentication process is based on the PKI of the cellular network.

C. MAC layer

Access control is an important component in D2D communications security. In out of coverage network extension or public safety scenarios, UEs have to become eligible to replace the role of the base station in term of resource allocation and controlling signal [START_REF] Bourrous | URA-MAC a new strategy for D2D communications[END_REF]. On another side, since cellular and D2D communications occur on the shared spectrum (licensed band), mutual interference appears to be harmful. However, D2D communications can be introduced as interference against eavesdroppers [START_REF] Ma | Interference exploitation in D2D-enabled cellular networks: a secrecy perspective[END_REF]. Thus, the secrecy capacity which quantifies the security of transmission of both D2D and cellular communications can be preserved and even improved which consequently increases the corresponding throughput [START_REF] Yue | Secrecy-based access control for Device-to-Device communication underlaying cellular networks[END_REF].

Other works considered an access control issue under the framework of multi-priority model which assigns highest priority to cellular users and multiple levels of priority for D2D ones [START_REF] Huang | Modeling and analysis on access control for Device-to-Device communications in cellular network: A network calculus based approach[END_REF][START_REF] Huang | A Priority-Based Access Control Model for Device-to-Device Communications Underlaying Cellular Network Using Network Calculus[END_REF], where Network Calculus theory was employed to model and analyze the access control for D2D communications underlaying cellular networks. Besides, access control can be used as a solution to preserve location and identity privacy in D2D communications [START_REF] Haus | Security and privacy in Device-to-Device (D2D) communication: a review[END_REF].

D. Physical layer

Developing security features at physical layer lead to enforce the security of upper layers and thus improve overall D2D communications. Chanel State Information (CSI) which refers to known channel properties of a wireless link can serve to extract secret keys from the measurement of physical layer. Recently, various CSI-based key extraction works have been proposed to secure D2D communications [START_REF] Abualhaol | Securing D2D Wireless Links by Continuous Authenticity with Legitimacy Patterns[END_REF][START_REF] Xi | KEEP: Fast secret key extraction protocol for D2D communication[END_REF][START_REF] Sun | SYNERGY: A game-theoretical approach for cooperative key generation in wireless networks[END_REF][START_REF] Zhu | Devicetodevice communications: The physical layer security advantage[END_REF][START_REF] Zhang | Radio resource allocation for physical-layer security in D2D underlay communications[END_REF][START_REF] Wang | physical layer security of D2D communications underlaying cellular networks[END_REF]. Xi et al. proposed in [START_REF] Xi | KEEP: Fast secret key extraction protocol for D2D communication[END_REF] Fast Secret Key Extraction Protocol for D2D Communication (KEEP), in which a validation-recombination mechanism is used to obtain symmetric secret keys from the CSI measurements of all OFDM subcarriers. The protocol achieves high security level against eavesdropping and predictable channel attacks. Authors in [START_REF] Sun | SYNERGY: A game-theoretical approach for cooperative key generation in wireless networks[END_REF] studied secret key establishment between two devices in D2D communications and proposed SYNERGY, a game-theoretical approach in order to stimulate cooperative key generation and to face the attitude of self-interesting nodes which are reticent to act as relays.

In order to emphasize instead the enforcement security that D2D paradigm can achieve via the physical layer, authors in [START_REF] Zhu | Devicetodevice communications: The physical layer security advantage[END_REF] derived the secrecy outage probability (SOP) for the D2D and cellular networks and compare performance for D2D scenarios in the presence of multi-antenna eavesdropper. Zhang et al. considered in [START_REF] Zhang | Radio resource allocation for physical-layer security in D2D underlay communications[END_REF] physical-layer security in D2D underlaying cellular networks and shown that D2D communications can lift the system secrecy capacity to a higher level.

In [START_REF] Wang | physical layer security of D2D communications underlaying cellular networks[END_REF] a novel resource allocation based on physical layer security was proposed, in which a power and subcarrier allocation scheme maximizes the D2D security capacity without influencing the cellular user's basic capacity. Jayasinghe et al. designed a secure beamforming technique to prevent eavesdropping on MIMO D2D communication via trusted relay which performs physical layer network coding [START_REF] Jayasinghe | Physical layer security for relay assisted MIMO D2D communication[END_REF].

Authors in [START_REF] Ma | Interference exploitation in D2D-enabled cellular networks: a secrecy perspective[END_REF] considered a large-scale D2D-enabled cellular network with presence of eavesdroppers overhearing cellular communications which was modeled using stochastic geometry. In order to guarantee performances of secure cellular communications, they proposed strong and weak performance guarantee criteria. In [START_REF] Sun | Two birds with one stone: Towards secure and interference-free D2D transmissions via constellation rotation[END_REF] a security-embedded interference avoidance scheme was proposed based on the concept of constellation-rotation which provides an inherent secrecy protection at the physical layer for both D2D and cellular users. Authors in [START_REF] Zhang | Joint power and access control for physical layer security in D2D communications underlaying cellular networks[END_REF] investigated the physical layers security issue in D2D communications underlaying cellular networks from a joint optimization perspective. They proposed a secrecy-based joint power and access control scheme with optimum D2D pair selection mechanism for cellular communication links and D2D pairs. Zhang et al. proposed in [START_REF] Zhang | Secrecy-optimized resource allocation for Device-to-Device communication underlaying heterogeneous networks[END_REF] a radio resource allocation solution which improves the secure capacity of D2D users underlaying heterogeneous networks.

The work in [START_REF] Abualhaol | Securing D2D Wireless Links by Continuous Authenticity with Legitimacy Patterns[END_REF] contributes to D2D security by employing the concept of continuous authenticity and proposing a security scoring system for measuring security. This solution is based on legitimacy patterns which are sent continuously to confirm and maintain the legitimacy of involved devices in D2D communications.

V. DISCUSSION

By reviewing many of recent works related to security in D2D communications, we notice that these works are scattered depending on some specific security issues in different security aspects and contexts. The majority of works related to the application layer have treated cryptographic key management issues in order to apply them in specific context. From the cryptographic point of view, key management schemes are important to find efficient cryptographic solutions in order to satisfy requirements in terms of authentication, confidentiality, integrity and so on. Proposed solutions in the literature didn't assume all scenarios related to the involvement of cellular infrastructure (i.e. assisted, controlled or autonomous), all the more difficulties concern keys distribution and revocation problems. It is judicious to reuse security solutions ensured by a cellular infrastructure, but in the same time theses solutions may work in case of out of coverage scenario.

In out of coverage scenario, techniques used in the proposed key management schemes are inspired from those used on the context of Wireless Sensor Networks (WSN) and Mobile Adhoc Networks (MANET), such as Diffie-Hellman based key exchange, IBE-ECC, CP-ABE and probabilistic key management schemes. However, D2D communications may gain advantage from the controlling or assistance of a cellular infrastructure by getting necessary credentials to be employed in case of intermittent cellular connectivity or out of coverage scenario. On the other side, local social networks have attracted increasing attentions from researchers in recent years. In order to face privacy issues in this type of scenario, clustering and coalition formation are the main approaches developed for this purpose.

Generally, D2D communications rely on one hop routing; however in different scenarios (public safety, extension of coverage, dissemination of content, etc.) they may rely on multi-hop routing. Few works in the literature have treated routing aspect in D2D communications. From the security point of view, much work remains to be done, especially to face security threats related to the absence of trust authority, and the highly dynamic of the topology on one hand; and on another hand to preserve security and privacy of users which will seen their sensitive information transit different nodes without trust authority. Besides, malicious contents can be injected into the D2D network and affect UEs with viruses, malwares and so on. Secure D2D routing through a cryptography approach needs manipulating cryptographic keys in such a way key management schemes may take into account. Another approach to secure routing in D2D communications relies on network coding which employs data splitting and shuffling mechanisms over butterfly networks. Physical layer security is playing a key role for securing wireless communications in recent years. It exploits physical characteristics of wireless channel to prevent essentially from eavesdropping attack without utilizing cryptographic approaches. Works related to this field turn around theoretic secrecy capacity, CSI-based authentication and CSI-based key agreement.

VI. CONCLUSION

D2D is promising technology in LTE-A networks. Taking advantage of proximity devices, it offers high throughput, lower delays and offloading cellular networks traffic. On the other side, it offers a variety of practical services (advertising and commercial services, public safety services, etc.). There are many design challenges in D2D so that much research effort is still needed. Security in D2D communication is still in an embryonic state. Few works have handled security issues in this novel technology. We are interesting in this paper to underline the necessity to develop a security solution which fulfills all security requirements, faces all security threats and supports all D2D communication scenarios. Thus, significant efforts must be provided in order to overcome seriously D2D security problems.

Figure 2 .

 2 Figure 2. The basic architecture of the EPS in 3GPP.

Figure 3 .

 3 Figure 3. The basic architecture of the ProSe underlaying 3GPP's EPS.

Figure 4 .

 4 Figure 4. Classification of D2D communications.

Figure 5 .

 5 Figure 5. Classification of D2D communications. A. Application layer In this layer, key management scheme is considered as the foundation of any solution based on cryptography. Various solutions have been proposed in literature [21-23, 25, 33-25, 39, 40, 48] (Table.1).

  1).

Table 1 .

 1 Application layer.

Table 3 .

 3 MAC and network layer.

Availability

Eavesdropping

Chen et al. studied in [START_REF] Chen | Exploiting Social Ties for Cooperative D2D Communications: A Mobile Social Networking Case[END_REF] cooperative D2D communications based on social trust and social reciprocity. Authors target a multi-hop D2D communication scenario for relaying purpose and develop a novel coalitional gametheoretical framework. They prove the existence of a core solution and propose a mechanism to implement it by identifying reciprocal cycles, each of which contains the nodes motivated to act as relay for others in the same cycle. In [START_REF] Zhang | Social Network Aware Device-to-Device Communication in Wireless Networks[END_REF], authors proposed a novel social-aware approach for optimizing D2D communication based on social network and physical wireless network layers.