Abstract

False data injection (FDI) attacks are crucial security threats to smart grid cyber-physical system (CPS), and could result in cataclysmic consequences to the entire power system. However, due to the high dependence on open information networking, countering FDI attacks is challenging in smart grid CPS. Most existing solutions are based on state estimation (SE) at the highly centralized control center; thus, computationally expensive. In addition, these solutions generally do not provide a high level of security assurance, as evidenced by recent work that smart FDI attackers with knowledge of system configurations can easily circumvent conventional SE-based false data detection mechanisms. In this paper, in order to address these challenges, a novel distributed host-based collaborative detection method is proposed. Specifically, in our approach, we use a conjunctive rule based majority voting algorithm to collaboratively detect false measurement data inserted by compromised phasor measurement units (PMUs). In addition, an innovative reputation system with an adaptive reputation updating algorithm is also designed to evaluate the overall running status of PMUs, by which FDI attacks can be distinctly observed. Extensive simulation experiments are conducted with real-time measurement data obtained from the PowerWorld simulator, and the numerical results fully demonstrate the effectiveness of our proposal.

Highlights

  • LJďĞƌ ^ƉĂĐĞ ^ĞŶƐŝŶŐ ĂƚĂ EĞƚǁŽƌŬƐ ĐƚƵĂƚŝŽŶ ŽŵŵĂŶĚƐ WŽǁĞƌ 'ƌŝĚexisting false data detection (FDD) approaches may be ineffective against newer or emerging False data injection (FDI) attacks

  • We propose a distributed host-based collaborative detection (DHCD) method based on rule specifications, rather than state estimation (SE)

  • DHCD can re38 duce the computational burden of the control center (CC), and achieve fast FDD and the 39 capability to evaluate the running status of meter devices

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Summary

Introduction

Existing FDD approaches may be ineffective against newer or emerging FDI attacks. A small number of hierarchical or distributed FDD schemes are de signed to reduce the computation requirements at the CC [16, 17], most of them are still based on SE; vulnerable to smart attackers. Another limitation of legacy FDD methods is that some prevailing countermeasures against cyber intrusion only aim to detect the “bad” data without further evaluating the true running status of the meter devices that might already be compromised by ma licious attackers [12, 16, 18].

64 2. Related Work
13: Compute updating reputation level by:
Conclusions
436 References
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