Securing Demand Response Management: A Certificate-Based Access Control in Smart Grid Edge Computing Infrastructure

The edge computing infrastructure has enabled a massive amount of data in the smart grid environment by a large number of connected automated devices to be processed at the edge of the network in proximity to the data generation source. The demand response management is a fundamental requirement for an efficient and reliable smart grid environment, which can be accomplished by the transfer of data between smart devices and the utility center (UC) in a smart city, very frequently. However, this frequent data transfer is subject to multiple threats including the tempering. Several authentication schemes were proposed to secure smart grid environment. However, many such schemes are either insecure or lack the required efficiency. To counter the threats and to provide efficiency, a new authentication scheme for demand response management (DRMAS) is proposed in this paper. DRMAS provides all necessary security requirements and resists known attacks. The proposed DRMAS is provably secure under formal analysis supplemented by a brief discussion on attack resilience. Moreover, the DRMAS completes the authentication procedure in just 20.11 ms by exchanging only 2 messages.


I. INTRODUCTION
Smart grid (SG) is envisioned to be the next generation power systems providing a seamless integration of cyber physical systems, information and communication technologies (ICT), and power generation and distribution domains. This advanced power grid system provides a bidirectional flow of energy between clients and utility service providers, and as a result the power consumption may be controlled and optimized in accordance with the real-time needs of the customer, which is productive for both customer as well as power generation domains. In comparison with conventional power grid, the SG-based system has advanced sensing and computing devices including sensors, actuators etc., for generating The associate editor coordinating the review of this manuscript and approving it for publication was Maode Ma . and transmitting the bidirectional flow of power-related realtime information. In SG-based system, there exist various levels of data flow to manage the demand response (DR). The short range communication technologies such as Zigbee, Bluetooth, Infrared, and 6LowPAN constitute the first level of information flow, while medium and long-range wireless communication networks such as LTE/LTE-A, WiMax, WiFi, and cellular networks represent the second level of information flow [1], [2]. These two levels of information flow for respective technology networks provide intelligent communication architecture for bridging the gaps between demand and supply of electric power on real-time basis. A typical smart grid architecture is shown in Fig. 1. It is worthy to note that by utilizing DR the SG may convey the real-time information regarding the ideal price of electricity at regular time intervals (every 10-15 min) to enable the users to adjust the power usage accordingly. This could massively help the stakeholders in conserving energy and reducing overhead costs. Besides, the SG-based system increases the reliability, transparency and efficiency of the electric power system. The handling of SG-based big data with CPSS can greatly help in insightful decisions leading to more productivity for all stakeholders, and ultimately enrich the living environments as well as user experiences [3]. In the smart grid infrastructure, security has been one of the big concerns because most of the SG systems operate over insecure communication-based public network [4]- [7]. An adversary may comfortably intercept the information over these channels, and could initiate different attacks to recover the user's secret information. Such reliance of SG systems on public networks may land the stakeholders into troubles. To address those security issues, there must be robust communication infrastructure in the form of authentication protocols, supporting secure information exchange among the legitimate entities and maintaining the privacy as well [8]- [10].
In recent years many authentication protocols for SG environment can be witnessed. In this connection, a key distribution protocol for identity-based signature and encryption has been demonstrated by Odelu et al. [11]. This protocol supports mutual authentication by constructing an agreed session key between smart meters (SMs) and the utility service provider. However, according to Tsai and Lo [12] the scheme proposed in [11] is vulnerable to session specific temporary information threat, and in return may compromise the privacy of SMs on revealing secret credentials. Besides, countering the security drawbacks in [11], the Odelu et al. presented an improved SG-based authentication protocol. Later, Doh et al. [13] designed an authenticated key agreement scheme ensuring mutual authenticity to both participants, SM and UC. Afterwards, Saxena et al. [14] presented a scheme for smart grid systems making certain the security against insider and outsider threats as posed to the SG environment. Later, He et al. [15] presented an elliptic curve cryptography (ECC)-based key distribution protocol for SGs ensuring anonymity to the stakeholders. This scheme has comparatively low computational and communicational overheads in comparison with Tsai and Lo's scheme [11]. In [16], Ali et al. presented an identity-based key management scheme employing elliptic curve cryptography to enhance the security of smart grid systems. However, Mahmood et al. [17] found that the scheme presented in [16] has serious weaknesses including the exposure of trusted authority's master key and is prone to many related attacks. Similarly, Mahmood et al. [18] also employed ECC to present a lightweight authenticated key agreement protocol to secure the interaction among clients and substations in the smart grid system. Nevertheless, Abbasinezhad-Mood and Nikooghadam [19] found that [18] does not comply with perfect forward secrecy, and was proved to be susceptible under CK adversarial model. Mahmood et al. presented another scheme [20], the authors in [21] argued that Mahmood et al.'s scheme [20] is vulnerable to ephemeral secret leakage and impersonation attacks. In 2018, another scheme [22] to provide security in SG environment was proposed by Challa et al. However, Chaudhry et al. [23] stated that the scheme [22] is unable to provide authentication between two entities of SG and has some other critical issues. The scheme of Chaudhry et al. [23] requires intervention of third party for establishing a secure connection between two SG devices. In 2019, Kumar et al. [24] proposed yet another temporal credential and ECC based authentication scheme for securing demand response management. However, the inherited incorrectness in their scheme to accommodate only one smart meter may restrict it's practical deployments and the obvious lack of initial verification on UC side, can encourage an adversary to force UC to process illegal requests [25].

A. MOTIVATIONS AND CONTRIBUTIONS
The SG-based system relies on internet-oriented communication and networking which renders the SG infrastructure vulnerable to several attacks including forgery attacks, impersonation attacks, man-in-the-middle attacks and replay attacks. This strong reliance of deployed smart meters (SMs) on ICT raise the same security concerns as already posed to ICT-based paradigms. These security loopholes may create gaps between demand and supply of power if exploited by malicious intruders. Furthermore, these might lead to misleading forecasting models and findings related to DR management. Thus, there is dire need to restrain the probability of different known threats to provide a smooth flow to smart grid operations in terms of DR and data analytics. Most of the existing schemes for securing DR in SG environments are either vulnerable to many security threats or suffer from high computation and communication costs; mainly due to underlying pairing based operations. Therefore, we desperately need an authenticated key agreement protocol for SG environment supporting the SG device validation as well as the dynamic addition of Utility Centre (UC). For securing the demand response (DR) management, in this paper, we propose an authentication scheme DRMAS which can mitigate pitfalls of existing schemes. The research contributions are illustrated as under: 1) A new certificate based authentication scheme DRMAS is proposed to manage demand response in smart grid-based systems, which makes certain the exchange of sensitive information only after a mutually agreed session key is established between SG device and UC. The proposed scheme is free of any costly pairing based operations and completes authentication by exchanging only two messages. 2) We employed a universally accepted Real-or-Random (ROR) model [26], [27] to formally verify the security features.
3) The informal security analysis of the contributed scheme is also presented to prove the resistance of the scheme against all known attacks. 4) We compare the performance and security features of the proposed DRMAS and related schemes.

B. THREAT MODEL
We employ the Dolev-Yao threat model [26] in our proposed protocol. Employed in a variety of protocols, [28]- [34], this model assumes an insecure public channel that is used by the communicating participants. Precisely, An adversary A may take this opportunity to misuse the intercepted communication data, since A might eavesdrop, replay, alter or delete any data during transmission by acting as an intermediary between the legal parties. Assuming, the smart devices are not tamper resistant, and the adversary could recover the stored contents from SG devices using power analysis attacks [35], [36]. We assume the trust authority (TA) to be fully trusted, and the utility centre (UC) as semi-trusted since both of these entities may not be compromised by the attacker.

II. DRMAS: PROPOSED SCHEME
This section explains the proposed DRMAS for securing demand response management in smart grid environments. Proposed DRMAS as depicted in Fig. 2 is detailed as follows:

A. SYSTEM SETUP
To accomplish the setting up of the system, the trusted authority T A selects an elliptic curve E p (α, β) over finite field Z p along with a base point G ∈ E p (α, β) of large order n s.t. n.G = O (a point at infinity). The p is selected as a very large prime number satisfying 4α 3 − 27β 2 =0 mod p. T A then selects x as private and Q = xG. as its' own public key.T A also selects a secure one way function h(·) and finally, publishes

B. UC REGISTRATION
For registering each UC j : {j = 1, 2..n}, T A selects unique ID j , private key p rj and computes public key

D. AUTHENTICATION
In Proposed DRMAS scheme, SD i initiates authentication phase to furnish a secure session key with UC j . The steps as illustrated in Fig. 2 and briefed below are performed between SD i and UC j to complete this phase: PDR 1: SD i → UC j : {m 1 } SD i selects r i ∈ Z * p randomly and generates current timestamp T 1 . SD i then compute U i = r i G and W i = r i P uj = r i p rj G along with the timestamp based random UC j after receiving m 1 , first verifies message freshness by checking |T 1 − T * 1 | ≤ 0, and upon success UC j computes Compute W i = p rj U i and ID i = ID i ⊕ W i . UC j checks existence of ID i in verifier database and on succes extracts RID i . UC j then checks the genuineness of random certificate as C s G , aborts the session, if any of these is invalid. Otherwise, UC j select r j ∈ Z * p , T 2 and computes U j = r j G, W j = r j U i = r i r j G, and session key PDR 3: UC j after receiving m 2 , first verifies message freshness by checking |T 3 − T * 3 | ≤ 0, and upon success UC j computes W j = r i U j = r i r j G, and ses- , on success UC j considers SD i as legal and authenticated device.
between SD i and UC j in mutual authentication phase. However, the involvement of timestamps T 1 and T 2 in respective authentication messages m 1 and m 2 , refrains the adversary to store and initiate replay attack at some future time. In that case, the legal participants may check the timestamp of message and abort the session, thereafter. Hence, the contributed scheme is protected from replay attack.

B. STOLEN SG DEVICE ATTACK
An adversary may steal or physically compromise the SG device, since these devices are normally deployed in the proximity of home or nearby places. Then the former may recover the critical contents of the SG device, such as . . n}, h(·)} by using power analysis attacks [35]- [37]. Here, , Q = xG, and Pu j = Pr j .G. Using the RID i and C i parameters, it would be computationally hard for the adversary to recover the device identity ID i without having access to UC j 's secret key x. It is worthy to note that RID i is unique for different SG devices due to distinct identities ID i for every SG device. Hence, despite accessing any stolen SG device contents, A could not compute the session key as established between UC and a non-compromised SG device. Therefore, our scheme is resistant to stolen SG device attack.

C. SG DEVICE IMPERSONATION ATTACK
An adversary may attempt to launch a SG device (SD i )impersonation attack by submitting an authentication request message towards UC j . For constructing this message, it may generate a random integer r A i ∈ Z * p and a fresh timestamp T 1 , and then compute where Pu j is the public key of UC i . However, to construction of a valid authentication request m 1 which is not possible until it gains access to some crucial parameters such as RID i , C i , and ID i . This depicts that the proposed scheme is protected from SG device impersonation attack.

D. MAN-IN-THE-MIDDLE ATTACK
An adversary may attempt to maneuver the intercepted messages by introducing suitable modifications in the message contents to impersonate the legal parties on both ends. In our scheme, the adversary, upon receiving the authentication request m 1 = {ID i , H i , U i , C s , T 1 } from SD i , may generate a random integer r a ∈ Z * p and a fresh timestamp T a , and then compute U a = r a .G. However, for constructing a legal authentication request m 1 = {ID i , H i , U a , C s , T a } it requires to compute a valid parameters, i.e., C s , H i and ID i , i.e. C s = r a T 1 + C i , H i = h(U a ||W i ||C s ||RID i ||T 1 ) and ID i = ID i ⊕ W i , which is computationally not feasible until the secret credentials RID i , C i , and ID i are accessed. Likewise, A may also attempt to modify the acknowledgment authentication message m2 = {U j , H j , T 2 } according to fresh timestamp T 2 . However, the involvement of secret credential RID i in the calculation of H j refrains the adversary to construct a fake acknowledgment message. Hence, the contributed scheme is immune to man-in-the-middle attack.

E. UC IMPERSONATION ATTACK
To impersonate as UC j , the adversary needs to construct a valid acknowledgment authentication message m 2 = . The adversary may generate a random number r A j and fresh timestamp T 2 , then it may further compute Nevertheless, the use of secret credential RID i debars the adversary to compute SK ij and in return H j , which nullifies the chances of the adversary's constructing a valid m 2 = {U j , H j , T 2 } message. Thus, our scheme is protected from UC j impersonation attack.

F. SESSION KEY SECURITY
In authentication phase of proposed model, the session key SK ij is established with secure mutual communication between SD i and UC j as SK ij = h(W j ||U j ||RID i ||U i ||W i ||T 2 ), where W j = r j U i = r i r j G, U j = r j G, RID i , U i and W i = pr j U i . It is evident that the strength of computed session key is based upon two constituent factors: 1) temporary secrets r i and r j , and 2) long term secret parameters such as pr j and RID i . It is worthy to note that in our protocol, the identities such as ID i and ID j , and master secret key x of TA are only known to the TA. We may consider the following two cases regarding the robustness of session key.
Case 1: In case, the temporary session variables r i and r j are revealed to the adversary, the session key SK ij is hard to compute for the adversary due to lacking long term secrets RID i and pr j .
Case 2: Likewise, in case the long term secret parameters such as RID i and pr j are revealed to the adversary, the SK ij still remains hard to compute for the adversary due to lacking temporary session variables r i and r j . While, these variables r i and r j are protected in U i and U j , respectively, since it is computational hard to recover r i and r j from U i and U j due to non-breakable security feature of elliptic curve discrete logarithm problem (ECDLP).
If we take the assumptions of both cases combined, i.e. the temporary session variables (r i and r j ) as well as long term secret parameters (RID i and pr j ) are revealed to the adversary, only then the later would be able to compute the legitimate session key. Moreover, if the current session key SK ij as established between the participants, is revealed to the adversary, then the later may not be able to compute the session keys of other sessions between the same parties, since every authentication session bears the unique temporary session variables. Hence, it would be unlikely for the adversary to be able to compute the previous or future session keys from the current revealed session key. In this manner our scheme provides perfect forward as well as backward secrecy to the legal participants.

G. ANONYMITY AND UNTRACEABILITY
In proposed scheme, an adversary may eavesdrop the communication messages m 1 = {ID i , H i , U i , C s , T 1 } and m 2 = {U j , H j , T 2 } over an insecure channel. However, A might not be able to derive the smart device's identity ID i from the exchanged messages, which is one of the crucial requirements in the security of smart grid system for the customer. Moreover, A may also be unable to distinguish the message contents of a session from other sessions either established between the same or different participants. This property ensures that a smart device may not be traced by the adversary. This is because of the fact, the parameters in m 1 and m 2 messages involve either current timestamps (T 1 and T 2 ) or fresh nonces (r i and r j ), respectively.

IV. FORMAL SECURITY ANALYSIS
Over the past few years, the security analysis under formal methods has got popularity and is being considered as the main strong proofing method. The popular Real-Or-Random (ROR) [26], [27] model is adopted here to prove the security of propose DRMAS. In DRMAS, there are three entities of environment, T A, SG device SD i and UC j . In ROR model the following ingredients are described below.

A. PARTICIPANTS
Let I x T A , I y SD i and I z U C j be the instances x, y and z of T A, SD i and UC j , which is called oracles. VOLUME 8, 2020 B. ACCEPTED STATE I x being an instance is considered as accepted, the accept state is achieved after last message is received during protocol execution. The (sid) of I x is termed as session identifier and is the ordered concatenation of all communication messages (received or sent) for a current session.

C. PARTNERING
Let I x 1 and I x 2 are known to be partnered, once the following three states are occurred simultaneously.
1) I x 1 and I x 2 are in accept state.
2) I x 1 and I x 2 are mutual authenticate and share identical (sid) with each other.
3) Both I x 1 and I x 2 are mutual partners.

D. FRESHNESS
Both instances I y SD i and I z U C j are fresh, if SK ij (session key) between SD i and UC j is not exposed to an attacker A using the query R(I x ) defined below.

E. ADVERSARY
Following ROR model, A is supposed to fully control all communications and can also use the following defined queries to eavesdrop, modify, manufacture and inject messages [27]: 1) Execute(I x , I y ): It is simulated as eavesdropping attack in which after execution of such a query, A can collect the transmitted messages.
2) Reveal(I x ): The current session key SK ij generated by x (and its partner) is revealed to A on execution of this query.
3) Send(I x , msg): By executing this, A being an active adversary can send msg to I x and can also receive the response. 4) Test(I x , msg): It represents the session key's (SK ij ) semantic security, under RoR's indistinguishability.
A gets SK ij from I x , on the successful running of an experiment involving an unbiased coin β flicked before start of the game, the output is known to A only, if SK ij is fresh and β = 1. Otherwise, A gets null value.

F. SEMANTIC SECURITY OF THE SESSION KEY
According to the requirements of ROR model, adversary needs to distinguish between an instance's original session key SK ij and a random key. A can allow several test queries to either I y SD i or I z UC j . Before the game finished, adversary returns the guessed bit b and A can win the game if condition b = b is matched. If SUC represents an event that adversary can win the game, the advantage adv AKA P of adversary in breaking the semantic security of the session key SK ij in our authenticated key-agreement AKA protocol, say P is represented and defined by Adv AKA P = |2.Pr[SUC] − 1|.P is said to be secure, Adv AKA P ≤ ψ, where ψ > 0 is a small real number.

G. RANDOM ORACLE
The legal entities as well A can access h(·), which is simulated as random oracle say HSH [27]. Following definitions are referred to prove the Theorem 1: Definition 1: Let a deterministic function h : {0, 1} * → {0, 1} u is collision resistant, which takes input v {0, 1} * with arbitrary length and produces h(v) {0, 1} of fixed length [38]. The advantage of A to find collusion is represented and defined by Adv HSH represents the probability of the event E represent. The the pair (b 1 , b 2 ) is selected randomly by A.The adversary A's advantage to made random choices within limited time bound tim is considered. The attack on collision resistance of h(.) by an ψ, tim-adversary is at most Adv HSH A (tim) ≤ ψ. Definition 2: Let G ∈ E p (α, β) is a point and given a quadruple (G, r i G, r j G, wG), decide whether w = r i r j or not is termed as the ECDDHP.
Theorem 1: Consider a polynomial time (tim) bound adversary A against the introduced DRMAS under ROR model If q hsh and |hsh| denote maximum numeral and range space of HSH queries and adv ECDDHP (x) expresses A's advantage to break ECDDHP. The advangate carried by A to break semantic security of SK ij in DRMAS is adv AKA DRMAS ≤ The number of HASH queries, the range space of hash function h(·) and the advantage of A in breaking the semantic security of the session key SK ij in P is adv AKA Proof: The proof resembles to the same presented in [24] and [27]. The in-sequences games G i : {i = 1, 2, 3, 4} are demarcated for the purpose of security analysis. Let SUC i be an event wherein A can correctly guess random bit β in G i . Details are as follows: Game 1 (G 1 ): G 1 simulates the actual attack launched by A against DRMAS under ROR model. Therefore, we have: Game 2 (G 2 ): simulates actual eavesdropping launched by A. The A can perform a query to Execute(I x , I y ) oracle. To complete G 2 , A queries the test oracle and result of test can confirm the correctness of SK ij . Note that SK ij is calculated by both SD i and UC j as SK ij = h(W j ||U j ||RID i ||ID j ||U i ||W i ||T 2 ). To calculate session key SK ij requires pair {y, z} (the ephemeral secrets), and W i , RID i and W j (the long-term secrets). Without this knowledge, deriving the session key SK ij is an impossible problem for A. Hence, winning chance of G 2 has not benefited by eavesdropping. Therefore, we have: Game 3 (G 3 ): G 3 models the real and active attack with additional Send(I x , msg) and hsh query simulations. A intends that a participant may accept the forged message. A is considered as capable enough to make different HO queries for examining the collision existence in hash. However, in login and authentication phase, all the messages H j , T 2 } and SK ij contain respective participant's identity, timestamps and random number. Hence, querying Send oracle do not return collision to A. The results of birthday paradox gives: Game 4 (G 4 ): G 3 is transformed into G 4 , where G 4 is the last game. it is modeled further as an active attack. As illustrated in G 2 , To calculate session key SK ij requires the ephemeral secrets y and z, and the long-term secrets W i , RID i and W j . Having the eavesdropping U i = r i G and U j = r j G, adversary requires to differentiate between r i r j G and a random number, which reduces to the ECDDHP problem. Hence, it is clear that the computation of SK ij depends on the ECDDHP problem. Its' result follow that In G 4 , all the random oracles are simulated. A is only left to guess β for winning the game after querying the Test oracle. Therefore, we have: From Equations 1 and 2, we have The triangular inequality and equations 3, 4, 5 give the following: From equations 6 and 7 finally, we have

A. COMPUTATION COST
For computation cost analysis, some notations are introduced. T epm , T epa , T h , T pb , T ex and T en represent ECC point multiplication, addition, hash, bilinear operation, exponentiation and symmetric encryption/decryption operations. For computation cost analysis, the experiment conducted on a PC with DUAL CPU E2200, 2.20 GHz processor, 2048 MB of RAM  implemented over Ubuntu OS with PBC Library by Kilinc and Yanik [39] is considered. As per [39], the running time of T bp = 5.811 ms, T ex = 3.85 ms, T epm = 2.226 ms, T epa = 0.0288 ms, T en = 0.0046 ms and T h = 0.0023. DRMAS has quite low computation cost as compared with [11], [12], [20] and has incurred extra computation time as compared with [22]- [24]. DRMAS complete a complete cycle of authentication in just ≈ 20.11 ms.

B. COMMUNICATION COST
For communication cost comparisons, some common assumptions regarding the sizes of different transmitted parameters are considered as: identity size is fixed at 160 bits, SHA − 1 is selected with 160 bits digest size, 160 bits long random number generation is selected; while the size of timestamp is taken as 32 bits long and the ECC points with 320 bits length are considered to provide same security as of RSA 1024 bits. Proposed DRMAS completes authentication through transmission of two messages: 1) m 1 = {ID i , H i , U i , C s , T 1 } from SD i to UC j , and m 2 = {U j , H j , T 2 } from UC j to SD i . The length of m 1 is {160+160+160+320+ 32} = 832 bits and the size of m 2 is {320 + 160 + 32} = 512. Therefore, total communication cost of DRMAS is 1344 bits, whereas, communication cost of scheme proposed by Kumar et al. [24] is 1376 bits. The communication costs of [11], [12], [20], [22] is 1408, 1920, 1536 respectively; whereas, the communication cost of scheme [23] is 2080 bits. Table 3 shows that DRMAS has lowest communication cost as compared with competitive scheme. Moreover, proposed DRMAS completes whole authentication process in just 2 messages, while all other schemes [11], [12], [20], [22]- [24] complete the same in 3 messages.

C. SECURITY FEATURES
The security features comparisons of the proposed DRMAS and competing schemes proposed in [11], [12], [20], [22]- [24] is depicted in Table 4   non-verification of initial message from SD i , UC j , the scheme proposed by Kumar et al. can become prey of an attacker bombardment of randomly generated illegal messages, which can eventually cause denial of services attack. As proved in [23], the scheme proposed in [22] suffers from incorrectness and no initial verification issues as of Kumar et al.'s scheme [24], the scheme proposed in [22] also lacks direct device to device (D2D) communication and requires intermediate party, which can become bottleneck for efficiency. Nevertheless, the scheme proposed in [23] also lacks direct D2D communication and scheme proposed in [20] lacks initial verification of request message. The scheme proposed in [12] lacks the procedure to add post-deployment dynamic addition of devices; whereas, citing [12], the scheme proposed in [11] is weak against privileged insider and does not provide anonymity and session key security. The scheme proposed in [11] also lacks the initial request message verification. Therefore, proposed scheme is best suitable for deployment in smart grid environments.

VI. CONCLUSION
In smart grid (SG), the demand response is maintained dynamically through exchanging data between entities. However, this data transfer requires an efficient and secure authentication scheme to avoid any modification over open channel.
To secure demand response management, we proposed an authentication scheme (DRMAS) using ECC based certificate. To prove the robustness, DRMAS is analyzed formally along with a discussion on security requirements to confirm formally and informally the robustness of the proposed scheme. DRMAS performs better in communication cost and achieves authentication in just 2 message exchanges. It is also shown that DRMAS provides best tradeoff between security and performance.   He is a leading authority in the areas of smart/intelligent, wireless, and mobile networks' architectures, protocols, deployments, and performance evaluation. His publication history spans over 250 publications in journals, conferences, patents, books, and book chapters, in addition to numerous keynotes and plenary talks at flagship venues. He has authored and edited more than 25 books about cognition, security, and wireless sensor networks' deployments in smart environments, published by Taylor and Francis, Elsevier, and Springer. He has received several recognitions and best papers' awards at top international conferences. He also received the prestigious Best Research Paper Award from Computer Communications (Elsevier) journal for the period 2015-2018, in addition to the Top Researcher Award for 2018 at Antalya Bilim University, Turkey. He has led a number of international symposia and workshops in flagship communication society conferences. He currently serves as an Associate Editor and the Lead Guest/Associate Editor for several well reputed journals, including the IEEE COMMUNICATIONS SURVEYS AND TUTORIALS (IF 22.9) and the Sustainable Cities and Society (Elsevier) (IF 4.7). VOLUME 8, 2020