Abstract
Providing adequate security measure during data transmission is one of the essential requirements of smart grid communication network (SGCN). In this paper, a novel trust management model is proposed to alleviate packet dropping attack between data aggregation points of SGCN. The concept of probability theory is used to calculate trust of every node in the network before transmitting the packet. Trust evaluation is conducted in four stages viz., Direct, Indirect, Integrated and Overall trust and in each stage, suitable equations are suggested to measure the trust of each node. A novel technique based on fuzzy set theory is used to route the packet through the trusted channel. Hop count, reliability and capacity of the link are the parameters considered for constructing if-then rules and membership function. A qualitative reasoning is performed using inference mechanism and a defuzzication strategy is applied on the calculated trust value to make decision. Simulations are carried out to evaluate the performance of the proposed approach by varying the trust threshold and malicious nodes. From the experiments, it is observed that for all the metrics, the proposed trusted routing using fuzzy theory helps to improve the network performance with much reliable communication and reduced packet loss.
Similar content being viewed by others
References
SGIP (2010) Introduction to NISTIR 7628 Guidelines for Smart Grid Cyber Security, 1–597. The Smart Grid Interoperability Panel Cyber Security Working Group, USA (2010)
Premaratne U, Samarabandu J, Sidhu T, Beresh R, Tan JC (2010) An intrusion detection system for IEC61850 automated substations. IEEE Trans Power Deliv 25:2376–2383
Akyol B, Kirkham H, Clements S, Hardley M (2010) A survey of wireless communications for the electric power system. Pacific Northwest National Laboratory, Richland, pp 1–73
Xie L, Mo Y, Sinopoli B (2010) False data injection attacks in electricity markets. In: Proceedings of IEEE conference on smart grid communications, Gaithersburg, MD, USA, pp 226–231
Yuan Y, Li Z, Ren K (2011) Modeling load redistribution attacks in power systems. IEEE Trans Smart Grid 2:382–390
Huang Y, Esmalifalak M, Nguyen H, Zheng R, Han Z, Li H, Song L (2013) Bad data injection in smart grid: attack and defense mechanisms. IEEE Commun Mag 51:27–33
Metke AR, Ekl RL (2010) Smart grid security technology. In: Proceedings of innovative smart grid technologies conference (ISGT), Gaithersburg, MD, USA, pp 1–7 (2010)
Guo H, Wu Y, Bao F, Chen H, Ma M (2011) UBAPV2G: a unique batch authentication protocol for vehicle-to-grid communications. IEEE Trans Smart Grid 2:707–714
Wang X, Yi P (2011) Security framework for wireless communications in smart distribution grid. IEEE Trans Smart Grid 2:809–818
Li Q, Cao G (2011) Multicast authentication in the smart grid with one-time signature. IEEE Trans Smart Grid 2:686–696
Kim YS, Heo J (2013) Device authentication protocol for smart grid systems using homomorphic hash. J Commun Netw 14:606–613
Diao F, Zhang F, Cheng X (2015) A privacy-preserving smart metering scheme using linkable anonymous credential. IEEE Trans Smart Grid 6:461–467
Locke G, Gallagher PD (2010) NIST framework and roadmap for smart grid interoperability standards, release 1.0, 1–145. Office of the National Coordinator for Smart Grid Interoperability, NIST Special Publication 1108, USA (2010)
Meng W, Ma R, Chen HH (2014) Smart grid neighborhood area networks: a survey. IEEE Netw 28:24–32
Ho QD, Gao Y, Le-Ngoc T (2013) Challenges and research opportunities in wireless communication networks for smart grid. IEEE Wirel Commun 23:89–95
Niyato D, Wang P (2012) Cooperative transmission for meter data collection in smart grid. IEEE Commun Mag 50:90–97
Akyildiz IF, Wang X (2005) A survey on wireless mesh networks. IEEE Commun Mag 43:23–30
IEEE Standard for Local and Metropolitan Area Networks (2009) IEEE Std. 802(16):1–2008
Xu Y, Wang W (2013) Wireless mesh network in smart grid: modeling and analysis for time critical communications. IEEE Trans Wirel Commun 12:3360–3371
Sun YL, Han Z, Liu KJR (2008) Defense of trust management vulnerabilities in distributed networks, security in mobile ad hoc and sensor networks. IEEE Commun Mag 46:112–119
Bellman RE, Zadeh LA (1970) Decision-making in a fuzzy environment. Manag Sci 17:B141–B164
Acknowledgments
This study was supported by the Brain Korea 21 Plus project (SW Human Resource Development Program for Supporting Smart Life) funded by Ministry of Education, School of Computer Science and Engineering, Kyungpook National University, Korea (21A20131600005).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Pugalendhi, G., Velusamy, D., Paul, A. et al. Fuzzy-based trusted routing to mitigate packet dropping attack between data aggregation points in smart grid communication network. Computing 99, 81–106 (2017). https://doi.org/10.1007/s00607-016-0518-5
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00607-016-0518-5