REACT to Cyber Attacks on Power Grids

Abstract

Motivated by the recent cyber attack on the Ukrainian power grid, we study cyber attacks on power grids that affect both the physical infrastructure and the data at the control center. In particular, we assume that an adversary attacks an area by: (i) remotely disconnecting some lines within the attacked area, and (ii) modifying the information received from the attacked area to mask the line failures and hide the attacked area from the control center. For the latter, we consider two types of attacks: (i) data distortion: which distorts the data by adding powerful noise to the actual data, and (ii) data replay: which replays a locally consistent old data instead of the actual data. We use the DC power flow model and prove that the problem of finding the set of line failures given the phase angles of the nodes outside of the attacked area is strongly NP-hard, even when the attacked area is known. However, we introduce the polynomial time REcurrent Attack Containment and deTection (REACT) Algorithm to approximately detect the attacked area and line failures after a cyber attack. We numerically show that it performs very well in detecting the attacked area, and detecting single, double, and triple line failures in small and large attacked areas.

Stochastic Defense Against Complex Grid Attacks

“…The possibility of cyber-or cyberphysical attacks on power grids has yielded mathematical work designed to detect and reconstruct such attacks. See [1] [2], [3], [4], [5], [6], [7], [8], [9], [10], [11], [12], [13], [14], [15], [16], [17], [18], [19].…”

“…the result of the attack is that sensors stop reporting, sophisticated techniques may still be brought to bear in order to identify, for example, the topology modification. See [14]- [17]. Most of the above work relies on the DC arXiv:1807.06707v14 [math.OC] 16 Oct 2018 (linear) model of power flows; the model in [16] (as far as we can tell) was the first to use the nonlinear AC power flows model.…”

“…Of course, the fewer the sensors the more limited the impact of the defense. Indeed, some interesting work (using the standard, DC-equation state estimation) precisely seeks to perform system identification post-attack when only limited sensor information is available [14], [15], [16], [17].…”

2019 Index IEEE Transactions on Network Science and Engineering Vol. 6

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PhishHaven—An Efficient Real-Time AI Phishing URLs Detection System

“…In [5], the authors focused on FDI(false data injection) attacks and how to mitigate such cyber attacks. And in [6], the authors investigated the effects of cyber attacks on power grids.…”