T 2 S 2 G: A Novel Two-Tier Secure Smart Grid Architecture to Protect Network Measurements

Israa T. Aziz, Hai Jin, Ihsan H. Abdulqadder, Sabah M. Alturfi, Wisam H. Alobaidi and Firas M.F. Flaih
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Israa T. Aziz: Cluster and Grid Computing Laboratory, Services Computing Technology and System Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
Hai Jin: Cluster and Grid Computing Laboratory, Services Computing Technology and System Laboratory, School of Computer Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
Ihsan H. Abdulqadder: The School of Information and Software Engineering, University of Electronic Science and Technology of China, Chengdu 610054, China
Sabah M. Alturfi: College of Law, University of Kerbala, Karbala 56001, Iraq
Wisam H. Alobaidi: State Company of the North Distribution Electricity, Ministry of Electricity, Baghdad 10013, Iraq
Firas M.F. Flaih: State Company of the North Distribution Electricity, Ministry of Electricity, Baghdad 10013, Iraq

Energies, 2019, vol. 12, issue 13, 1-24

Abstract: False data injection (FDI) attacks are a major security threat to smart grid (SG) communication systems. In FDI attacks, the attacker has the ability of modifying the measurements transmitted by smart grid entities such as smart meters, buses, etc. Many solutions have been proposed to mitigate FDI attacks in the SG. However, most of these solutions rely on centralized state estimation (SE), which is computationally expensive. To engulf this problem in FDI attack detection and to improve security of SGs, this paper proposes novel two-tier secure smart grid (T 2 S 2 G) architecture with distributed SE. In T 2 S 2 G, measurement collection and SE are involved in first tier while compromised meter detection is involved in second tier. Initially the overall SG system is divided into four sections by the weighted quad tree (WQT) method. Each section is provided with an aggregator, which is responsible to perform SE. Measurements from power grids are collected by remote terminal units (RTUs) and encrypted using a parallel enhanced elliptic curve cryptography (PEECC) algorithm. Then the measurements are transmitted to the corresponding aggregator. Upon collected measurements, aggregator estimates state using the amended particle swarm optimization (APSO) algorithm in a distributed manner. To verify authenticity of aggregators, each aggregator is authenticated by a logical schedule based authentication (LSA) scheme at the control server (CS). In the CS, fuzzy with a neural network (FNN) algorithm is employed for measurements classification. Our proposed T 2 S 2 G shows promising results in the following performance metrics: Estimation error, number of protected measurements, detection probability, successful detection rate, and detection delay.

Keywords: FDI attacks; power grid measurements; distributed state estimation; compromised meter; smart grid (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
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