Taxonomy of Threats and Vulnerabilities in Smart Grid Networks
Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.
[1] J. B. Ekanayake, N. Jenkins, K. Liyanage, J. Wu, and A. Yokoyama, Smart Grid: Technology and Applications. John Wiley & Sons, 2012.
[2] F. Skopik and P. Smith, Smart Grid Security: Innovative Solutions for a Modernized Grid. Elsevier Science & Technology Books, 2015.
[3] C. Greer et al., “NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 3.0,” National Institute of Standards and Technology, NIST SP 1108r3, Oct. 2014. doi: 10.6028/NIST.SP.1108r3.
[4] M. Uma and G. Padmavathi, “A Survey on Various Cyber Attacks and Their Classification,” p. 7, 2013.
[5] ETV 2 NITTTRCHD, Cyber Security in Smart Grid: Overview Session 1 Module 15 by Janorious Rabeela. 2019.
[6] D. Wei, Y. Lu, M. Jafari, P. M. Skare, and K. Rohde, “Protecting Smart Grid Automation Systems Against Cyberattacks,” IEEE Transactions on Smart Grid, vol. 2, no. 4, pp. 782–795, Dec. 2011, doi: 10.1109/TSG.2011.2159999.
[7] F. Aloul, A. R. Al-Ali, R. Al-Dalky, M. Al-Mardini, and W. El-Hajj, “Smart Grid Security: Threats, Vulnerabilities and Solutions,” SGCE, pp. 1–6, 2012, doi: 10.12720/sgce.1.1.1-6.
[8] M. Jouini, L. B. A. Rabai, and A. B. Aissa, “Classification of Security Threats in Information Systems,” Procedia Computer Science, vol. 32, pp. 489–496, Jan. 2014, doi: 10.1016/j.procs.2014.05.452.
[9] A. Sanjab, W. Saad, I. Guvenc, A. Sarwat, and S. Biswas, “Smart Grid Security: Threats, Challenges, and Solutions,” arXiv:1606.06992 (cs, math), Jun. 2016, Accessed: Mar. 06, 2021. (Online). Available: http://arxiv.org/abs/1606.06992.
[10] A. Takiddin, M. Ismail, U. Zafar, and E. Serpedin, “Robust Electricity Theft Detection Against Data Poisoning Attacks in Smart Grids,” IEEE Transactions on Smart Grid, pp. 1–1, 2020, doi: 10.1109/TSG.2020.3047864.
[11] L. Zhang, X. Shen, F. Zhang, M. Ren, B. Ge, and B. Li, “Anomaly Detection for Power Grid Based on Time Series Model,” in 2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Aug. 2019, pp. 188–192, doi: 10.1109/CSE/EUC.2019.00044.
[12] J. Jiang and Y. Qian, “Defense Mechanisms against Data Injection Attacks in Smart Grid Networks,” IEEE Communications Magazine, vol. 55, no. 10, pp. 76–82, Oct. 2017, doi: 10.1109/MCOM.2017.1700180.
[13] S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” in Proceedings of the 6th annual international conference on Mobile computing and networking, New York, NY, USA, Aug. 2000, pp. 255–265, doi: 10.1145/345910.345955.
[14] K. Paul and D. Westhoff, “Context aware detection of selfish nodes in DSR based ad-hoc networks,” in Proceedings IEEE 56th Vehicular Technology Conference, Sep. 2002, vol. 4, pp. 2424–2429 vol.4, doi: 10.1109/VETECF.2002.1040656.
[15] S. Bansal and M. Baker, “Observation-based Cooperation Enforcement in Ad Hoc Networks,” arXiv:cs/0307012, Jul. 2003, Accessed: Feb. 01, 2021. (Online). Available: http://arxiv.org/abs/cs/0307012.
[16] Y. B. Reddy, “A Game Theory Approach to Detect Malicious Nodes in Wireless Sensor Networks,” in 2009 Third International Conference on Sensor Technologies and Applications, Jun. 2009, pp. 462–468, doi: 10.1109/SENSORCOMM.2009.76.
[17] Yizhong Ma, Hui Cao, and Jun Ma, “The intrusion detection method based on game theory in wireless sensor network,” in 2008 First IEEE International Conference on Ubi-Media Computing, Jul. 2008, pp. 326–331, doi: 10.1109/UMEDIA.2008.4570911.
[1] J. B. Ekanayake, N. Jenkins, K. Liyanage, J. Wu, and A. Yokoyama, Smart Grid: Technology and Applications. John Wiley & Sons, 2012.
[2] F. Skopik and P. Smith, Smart Grid Security: Innovative Solutions for a Modernized Grid. Elsevier Science & Technology Books, 2015.
[3] C. Greer et al., “NIST Framework and Roadmap for Smart Grid Interoperability Standards, Release 3.0,” National Institute of Standards and Technology, NIST SP 1108r3, Oct. 2014. doi: 10.6028/NIST.SP.1108r3.
[4] M. Uma and G. Padmavathi, “A Survey on Various Cyber Attacks and Their Classification,” p. 7, 2013.
[5] ETV 2 NITTTRCHD, Cyber Security in Smart Grid: Overview Session 1 Module 15 by Janorious Rabeela. 2019.
[6] D. Wei, Y. Lu, M. Jafari, P. M. Skare, and K. Rohde, “Protecting Smart Grid Automation Systems Against Cyberattacks,” IEEE Transactions on Smart Grid, vol. 2, no. 4, pp. 782–795, Dec. 2011, doi: 10.1109/TSG.2011.2159999.
[7] F. Aloul, A. R. Al-Ali, R. Al-Dalky, M. Al-Mardini, and W. El-Hajj, “Smart Grid Security: Threats, Vulnerabilities and Solutions,” SGCE, pp. 1–6, 2012, doi: 10.12720/sgce.1.1.1-6.
[8] M. Jouini, L. B. A. Rabai, and A. B. Aissa, “Classification of Security Threats in Information Systems,” Procedia Computer Science, vol. 32, pp. 489–496, Jan. 2014, doi: 10.1016/j.procs.2014.05.452.
[9] A. Sanjab, W. Saad, I. Guvenc, A. Sarwat, and S. Biswas, “Smart Grid Security: Threats, Challenges, and Solutions,” arXiv:1606.06992 (cs, math), Jun. 2016, Accessed: Mar. 06, 2021. (Online). Available: http://arxiv.org/abs/1606.06992.
[10] A. Takiddin, M. Ismail, U. Zafar, and E. Serpedin, “Robust Electricity Theft Detection Against Data Poisoning Attacks in Smart Grids,” IEEE Transactions on Smart Grid, pp. 1–1, 2020, doi: 10.1109/TSG.2020.3047864.
[11] L. Zhang, X. Shen, F. Zhang, M. Ren, B. Ge, and B. Li, “Anomaly Detection for Power Grid Based on Time Series Model,” in 2019 IEEE International Conference on Computational Science and Engineering (CSE) and IEEE International Conference on Embedded and Ubiquitous Computing (EUC), Aug. 2019, pp. 188–192, doi: 10.1109/CSE/EUC.2019.00044.
[12] J. Jiang and Y. Qian, “Defense Mechanisms against Data Injection Attacks in Smart Grid Networks,” IEEE Communications Magazine, vol. 55, no. 10, pp. 76–82, Oct. 2017, doi: 10.1109/MCOM.2017.1700180.
[13] S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” in Proceedings of the 6th annual international conference on Mobile computing and networking, New York, NY, USA, Aug. 2000, pp. 255–265, doi: 10.1145/345910.345955.
[14] K. Paul and D. Westhoff, “Context aware detection of selfish nodes in DSR based ad-hoc networks,” in Proceedings IEEE 56th Vehicular Technology Conference, Sep. 2002, vol. 4, pp. 2424–2429 vol.4, doi: 10.1109/VETECF.2002.1040656.
[15] S. Bansal and M. Baker, “Observation-based Cooperation Enforcement in Ad Hoc Networks,” arXiv:cs/0307012, Jul. 2003, Accessed: Feb. 01, 2021. (Online). Available: http://arxiv.org/abs/cs/0307012.
[16] Y. B. Reddy, “A Game Theory Approach to Detect Malicious Nodes in Wireless Sensor Networks,” in 2009 Third International Conference on Sensor Technologies and Applications, Jun. 2009, pp. 462–468, doi: 10.1109/SENSORCOMM.2009.76.
[17] Yizhong Ma, Hui Cao, and Jun Ma, “The intrusion detection method based on game theory in wireless sensor network,” in 2008 First IEEE International Conference on Ubi-Media Computing, Jul. 2008, pp. 326–331, doi: 10.1109/UMEDIA.2008.4570911.
@article{"International Journal of Electrical, Electronic and Communication Sciences:80247", author = "Faisal Al Yahmadi and Muhammad R. Ahmed", title = "Taxonomy of Threats and Vulnerabilities in Smart Grid Networks", abstract = "Electric power is a fundamental necessity in the 21st century. Consequently, any break in electric power is probably going to affect the general activity. To make the power supply smooth and efficient, a smart grid network is introduced which uses communication technology. In any communication network, security is essential. It has been observed from several recent incidents that adversary causes an interruption to the operation of networks. In order to resolve the issues, it is vital to understand the threats and vulnerabilities associated with the smart grid networks. In this paper, we have investigated the threats and vulnerabilities in Smart Grid Networks (SGN) and the few solutions in the literature. Proposed solutions showed developments in electricity theft countermeasures, Denial of services attacks (DoS) and malicious injection attacks detection model, as well as malicious nodes detection using watchdog like techniques and other solutions.
", keywords = "Smart grid network, security, threats, vulnerabilities.", volume = "15", number = "4", pages = "99-4", }
