Conference Proceeding

Mathematics in Space and Applied Sciences (ICMSAS-2023)
ICMSAS-2023

Subject Area: Mathematics
Pages: 331
Published On: 03-Mar-2023
Online Since: 04-Mar-2023

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Author(s): Publish, Meenakshi

Email(s): thakurlovii0@gmail.com

Address: Publish, Meenakshi
Srinivasa Ramanujan Department of Mathematics, Central University of Himachal Pradesh, Dharamshala (176215), India
*Corresponding Author

Published In:   Conference Proceeding, Mathematics in Space and Applied Sciences (ICMSAS-2023)

Year of Publication:  March, 2023

Online since:  March 04, 2023

DOI:




Cryptanalysis of LSPA-SGs: A lightweight and secure protocol for authentication and key agreement based Elliptic Curve Cryptography in smart grids

 

Publish, Meenakshi

Srinivasa Ramanujan Department of Mathematics, Central University of Himachal Pradesh,

Dharamshala (176215), India

*Corresponding Author E-mail: thakurlovii0@gmail.com

 

ABSTRACT:

Smart grids are becoming more and more significant as more nations adopt the smart city concept and boost energy sector efficiency to create a more sustainable and secure  future. However, it is critical to address the security issues with smart grids. Security and privacy are essential components of SG communication. Recently, the LSPA-SGs scheme was created, and according to its creators, it is an effective and secure protocol. We reviewed their scheme and observed that it does not provide security and privacy. It contain some security vulnerabilities; user anonymity, stolen-verifier attack, password guessing attack, physical attack, privileged insider attack, user impersonation attack. This study exposed the weaknesses of Susan A. Mohammed et al design's and demonstrated how many security issues allowed for powerful attacks.

 

KEYWORDS: Smart grids, Elliptic curve cryptography, Authentication, key agreement, Security.

 

1 INTRODUCTION:

The first AC electric grid was built in Great Barrington, Massachusetts, in 1886 [1]. In this period, the distribution, transmission, and demand-driven regulation of energy were all handled by a single, consolidated grid. Local grids in the 20th century expanded throughout time and finally joined for practical and reliable reasons. Daily peaks in demand caused by residential heating and cooling were addressed by a variety of high-power generators that were only turned on briefly each day. Due to the low utilization of these peaking generators and the need for grid redundancy, gas turbines were typically used, which have lower capital costs and faster start up times. The electrical providers were hit with significant expenses as a result, which were subsequently passed on to customers in the form of higher prices. This electrical grid was not fulfilling the demands of 20th century populations due to a lack of natural gas, coal, water, and various fossil fuels, for which we had to introduce modern technology so that the electrical grid would become smarter. A better electrical power grid, a "smart grid," works with infrastructure communication technology to distribute electricity more effectively and to communicate with users and power communication providers. The 20th century's constantly evolving and expanding power needs cannot be met by the existing power grid architecture, making efficient power grid utilization essential today [1]. Among its many benefits, the smart grid allows for better management and expansion of renewable energy sources. Rapid advancements in communication and information technology in recent years have resulted in secure and ongoing technological advancements [2]. Just a few of the options it provides for developing a growing intelligent platform include power control, internet communication, and smart meters [3, 4]. A platform called SG enables two-way contact between users and service providers on a regular basis for computation and communication [5]. SG may be suspended from cyberattacks due to its sensitivity [6]. Physical attacks, cyberattacks, and natural disasters pose the greatest risks to the deployment of smart grids since they can result in blackouts, infrastructure failure, consumer data breaches, energy theft, and the safety of operating personnel, among other things [7]. As a result, extensive research is being done to increase the security of smart grids [8]. In order to provide solutions that are resistant to cyber-attacks in smart grid applications, security measures are essential [9, 10]. The smart grid security issue needs to be taken care of immediately. It is crucial to provide SG with a safe and secure authentication system that maintains trust between genuine users and satisfies other security requirements like anonymity authentication and privacy.

 

2. RELATED WORK:

Several models are being used in current study. The foundation for HAN and BAN authentication was created in 2011 by Fouda et al. This system uses exponential operations and time-consuming procedures like public key encoding and decoding. Weizheng Wang et al. created their system in 2011 by combining block chain technology with ECC. Khan proposed the PALAK smart grid system in 2020 [16], which is a unique system. They talked about a lot of PALK's security features and attack resilience. An efficient and secure design between the user and the utility centre was what Moghadam et al. sought to achieve in 2020 with their design for key agreement and authentication. Li et al. [13] created an anonymous authentication system for SG architects. The sender's identity and the multiplication of two points over the curve are both unknowns during the login and verification phase of the PALK system, SA Chaudhary [17] showed in 2021.Some smart grid-connected devices are unable to finish  a single authentication cycle as a result of the weaknesses in this protocol. Scheme [17] proposes an immediate remedy for the significant problems of the palak. However, [17] overlooked a few issues that may have been  fixed in  LSPA-SGs   [18] . Consequently, we provided the LSPA-SGs [18] cryptanalysis  in this work.

 

3. ORGANIZATION OF THE PAPER:

The paragraphs that make up the framework of the paper are as follows: Section 4 revisits the  [18]    system, and   Section 5    addresses its shortcomings. We summarize our conclusions in the final part.

 

Table 1   The meaning of the symbols

Symbols

Description

P

Base point on an elliptic curve

TA

Trust Authority

IDi

Identity (particular user)

ENC\DEC

Encryption\Decryption

PrT\PKT

Private key\public key (TA)

SKi\PKi

Private key\public key (participant)

SKij

Shared key (between participant)

 

4. THE BRIEF OVERVIEW OF SUSAN SCHEME:

Step 1:

The UA enters his identification (Id), password (Pw).Computes N and A, respectively, as well as P and verifies AA =?A. UA sets timestamp T1 and sends "AA,NA, T1" to UB over public channel if the verification step is successful.

 

Step 2:

After receiving AA, NA, and T1, the UB sets timestamp T2 and tests its freshness using the relation | T2-T1 |≤ ∆T. If this is successful, the UB chooses a random number, gB, and computes GB= gB.P, KB = gB.(AA+PKT+NA.PKT), SKBA = h(gB.AA||T2||qB), and AutB = h(SKBA||qB). Now, UB uses computed key KB to encrypt EB = ENCKB (qB||T2). Finally, UB transmits to UA "EB, GB, AutB, T2".

 

Step 3:

UA sets timestamp T3, and upon success, computes KA = SKA.GB and decrypts DEC(EB)KA = (qB, T2) to determine whether the timestamp is fresh. In addition, UA calculates SKAB=h(NA.GB||T2||qB), AutA = h(SKAB||qB), and confirm AutA =? AutB. In the event that the verification is successful, UA chooses the random number XA, computes FA = h(AutA||XA), and then encrypts EA = ENCKA(FA||XA) using the computed key KA. Then, UA uses a public channel to send "EA, FA, T3" to UB.

 

 

Step 4:

After receiving EA, FA, and T3 from UA, UB sets timestamp T4 and, upon success, determines if the timestamp is current using the relation | T4- T3|≤ ∆T, DEC(EA)KB = (AutA, XA). The authentication and session key are therefore successful if UB calculates FB = h (AutA||XA) and then verifies FB =? FA.

 

Password change phase:

The user provides his ID and PWi of choice in the registration process. After entering its ID, for example, entity A, one of the entities will then proceed. Using PWA, the parameters NA = h(IdA||PWA||aA) and AA = NA.P are calculated. Then, the verification between AA’ and AA is checked. Then the user enters his or her new password, say "PWA," and computes the relationships NA = h(IdA||PWA||aA) and AA = NA.P. If the computation is successful, Finally, parameter AA’ takes the place of parameter AA in the target entity's memory.

 

5. THE CRYPTANALYSIS OF SUSAN SCHEME:

This section demonstrates some security flaws discovered in the technique, including privileged insider, stolen verifies, password guessing, user impersonation, user anonymity, and password modification attacks.

 

5.1   Privileged insider:

In the literature, there are several schemes that demonstrate the viability of privileged insider attacks, as we stated in the security models. Therefore, the insider attack is practically valid in Susan's system. Because in the registration phase, Ui sends Idi, Ni to TA via secure channels. Then malicious insider might obtaining the information i.e Ni , Idi. and also extract the parameter xA, Ai from the memory using side channel attack. A can guess PWDi of Ui.

 

5.2 Password guessing attack:

Input the values of xi and Idi in Ni =h(Idi||PWi||xi), then the attacker guess the password by inputing the variable values to equating it with Ni value and thus, the  output is correct password PWDi of Ui. In this way, Attacker can register himself/herself with Ui’s Idi and PWDi.      

 

5.3 User impersonation attack:

Suppose A uses side channel attacks to obtain Idi and PWDi in addition to the parameters xi, Ai, and other information from the memory. Attacker A calculates Ni = h(Idi||PWi||xi) by first creating a random number yi in place of xi. Then through secure channel A send Idi , Ni to TA . After receiving Idi, Ni; TA computes Ai =Ni.P, Ci=PKT +Ai, hci =h(Ci), msi = PrT +hci*PrT and SKi = Ni +msi. TA sends Ci, PKT, SKi to Ui through secure channel. As a result of the judgement above, we can conclude that A uses a computer in a legal manner.

 

5.4 Password change phase:

The user first completes the registration process by entering the ID and PW of his choice. As of right now, A has entered his PW and ID, calculated Ni* and Ai*, and verified that Ai*=Ai. If successful (obviously), A enters its new password, i.e., Pwi**, computes all of these parameters (Ai**, Ni**), and replaces the parameters AA in the target entity's memory.

 

6. CONCLUSION:

In this study, we performed cryptanalysis on the Susan scheme and discovered a number of significant flaws that let attackers launch powerful attacks such as impersonation attack, password guessing attacks, privileged insider attacks, and password change attacks. To address these issues, we must encrypt that value, which is kept in the database (memory card). Attackers who gain access to the memory card will be unable to use the relation Ni=h(idi||PWi||ai) to determine the password of the desired user. If so, this approach is secure and also works with smart grid systems.

 

7. REFERENCES:

1.         Chr. Lamnatou, D. Chemisana, C. Cristofari, Smart grids and smart technologies in relation to photovoltaics, storage systems, buildings and the environment, Renew Energy 185 (2021) 1376–1391.

2.         Muhammed Zekeriya Gunduz, Resul Das, Cyber-security on smart grid: Threats and potential solutions, Comput Netw 169 (2020).

3.         M.Z. Gunduz, R. Das, Analysis of cyber-attacks on smart grid applications, in: 2018 international conference on artificial intelligence and data processing (IDAP), 2018, pp. 1–5.

4.         S. Garg, K. Kaur, G. Kaddoum, Secure and lightweight authentication scheme for smart metering infrastructure in smart grid, IEEE Trans Ind Inform (2019).

5.         M.H. Yaghmaee, A. Leon-Garcia, M. Moghaddassian, On the performance of distributed and cloud-based demand response in smart grid, IEEE Trans Smart Grid 9 (5) (2017) 5403–5417.

6.         K. Kimani, V. Oduol, K. Langat, Cyber security challenges for IoT-based smart grid networks, Int J Crit Infrastruct Prot 25 (2019) 36–49.

7.         Abdulrahaman Okino Otuoze, Mohd Wazir Mustafa, Raja Masood Larik, Smart grids security challenges: Classification by sources of threats, J Electr Syst Inf Technol 5 (2018) 468–483.

8.         I. Colak, S. Sagiroglu, G. Fulli, M. Yesilbudak, C.-F. Covrig, A survey on the critical issues in smart grid technologies, Renew Sustain Energy Rev 54 (2016) 396–405.

9.         S. Shitharth, D.P. Winston, A novel IDS technique to detect DDoS and sniffers in smart grid. In: Proc. world conf. futuristic trends res. innov. soc. welfare (Startup Conclave). 2016, p. 1–6.

10.      D. Ding, Q.-L. Han, Y. Xiang, X. Ge, X.-M. Zhang, A survey on security control and attack detection for industrial cyber–physical systems, Neurocomputing 275 (2018) 1674–1683.

11.      W. Wang, H. Huang, L. Zhang, C. Su, Secure and efficient mutual authentication protocol for smart grid under blockchain, Peer-to-Peer Netw Appl 14 (5) (2021) 2681–2693.

12.      Mostafa Farhadi Moghadam, et al., A lightweight key management protocol for secure communication in smart grids, Electr Power Syst Res 178 (2020) 106024.

13.      X. Li, F. Wu, S. Kumari, L. Xu, A.K. Sangaiah, K.-K.R. Choo, A provably secure and anonymous message authentication scheme for smart grids, J Parallel Distrib Comput (2017).

14.      D. Abbasinezhad-Mood, M. Nikooghadam, Design and extensive hardware performance analysis of an efficient pairwise key generation scheme for smart grid, Int J Commun Syst 31 (5) (2018).

15.      A. Braeken, P. Kumar, A. Martin, Efficient and provably secure key agreement for modern smart metering communications, Energies 11 (10) (2018) 2662.

16.      A.A. Khan, V. Kumar, M. Ahmad, S. Rana, D. Mishra, PALK: Password-based anonymous lightweight key agreement framework for smart grid, Int J Electr Power Energy Syst 121 (2020) 1–12.

17.      Shehzad Ashraf Chaudhry, Correcting PALK: Password-based anonymous lightweight key agreement framework for smart grid, Int J Electr Power Energy Syst 125 (2021) 1–6.

18.      LSPA-SGs: A lightweight and secure protocol for authentication and key agreement based Elliptic Curve Cryptography in smart grids Susan A. Mohammed Taqia, Saeed Jalilib https://doi.org/10.1016/j.egyr.2022.06.096




REFERENCES:

1.         Chr. Lamnatou, D. Chemisana, C. Cristofari, Smart grids and smart technologies in relation to photovoltaics, storage systems, buildings and the environment, Renew Energy 185 (2021) 1376–1391.

2.         Muhammed Zekeriya Gunduz, Resul Das, Cyber-security on smart grid: Threats and potential solutions, Comput Netw 169 (2020).

3.         M.Z. Gunduz, R. Das, Analysis of cyber-attacks on smart grid applications, in: 2018 international conference on artificial intelligence and data processing (IDAP), 2018, pp. 1–5.

4.         S. Garg, K. Kaur, G. Kaddoum, Secure and lightweight authentication scheme for smart metering infrastructure in smart grid, IEEE Trans Ind Inform (2019).

5.         M.H. Yaghmaee, A. Leon-Garcia, M. Moghaddassian, On the performance of distributed and cloud-based demand response in smart grid, IEEE Trans Smart Grid 9 (5) (2017) 5403–5417.

6.         K. Kimani, V. Oduol, K. Langat, Cyber security challenges for IoT-based smart grid networks, Int J Crit Infrastruct Prot 25 (2019) 36–49.

7.         Abdulrahaman Okino Otuoze, Mohd Wazir Mustafa, Raja Masood Larik, Smart grids security challenges: Classification by sources of threats, J Electr Syst Inf Technol 5 (2018) 468–483.

8.         I. Colak, S. Sagiroglu, G. Fulli, M. Yesilbudak, C.-F. Covrig, A survey on the critical issues in smart grid technologies, Renew Sustain Energy Rev 54 (2016) 396–405.

9.         S. Shitharth, D.P. Winston, A novel IDS technique to detect DDoS and sniffers in smart grid. In: Proc. world conf. futuristic trends res. innov. soc. welfare (Startup Conclave). 2016, p. 1–6.

10.      D. Ding, Q.-L. Han, Y. Xiang, X. Ge, X.-M. Zhang, A survey on security control and attack detection for industrial cyber–physical systems, Neurocomputing 275 (2018) 1674–1683.

11.      W. Wang, H. Huang, L. Zhang, C. Su, Secure and efficient mutual authentication protocol for smart grid under blockchain, Peer-to-Peer Netw Appl 14 (5) (2021) 2681–2693.

12.      Mostafa Farhadi Moghadam, et al., A lightweight key management protocol for secure communication in smart grids, Electr Power Syst Res 178 (2020) 106024.

13.      X. Li, F. Wu, S. Kumari, L. Xu, A.K. Sangaiah, K.-K.R. Choo, A provably secure and anonymous message authentication scheme for smart grids, J Parallel Distrib Comput (2017).

14.      D. Abbasinezhad-Mood, M. Nikooghadam, Design and extensive hardware performance analysis of an efficient pairwise key generation scheme for smart grid, Int J Commun Syst 31 (5) (2018).

15.      A. Braeken, P. Kumar, A. Martin, Efficient and provably secure key agreement for modern smart metering communications, Energies 11 (10) (2018) 2662.

16.      A.A. Khan, V. Kumar, M. Ahmad, S. Rana, D. Mishra, PALK: Password-based anonymous lightweight key agreement framework for smart grid, Int J Electr Power Energy Syst 121 (2020) 1–12.

17.      Shehzad Ashraf Chaudhry, Correcting PALK: Password-based anonymous lightweight key agreement framework for smart grid, Int J Electr Power Energy Syst 125 (2021) 1–6.

18.      LSPA-SGs: A lightweight and secure protocol for authentication and key agreement based Elliptic Curve Cryptography in smart grids Susan A. Mohammed Taqia, Saeed Jalilib https://doi.org/10.1016/j.egyr.2022.06.096



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Author/Editor Information

Dr. Sanjay Kango

Department of Mathematics, Neta Ji Subhash Chander Bose Memorial, Government Post Graduate College, Hamirpur Himachal Pradesh-177 005, INDIA