Smart grid data integrity attacks: characterizations and countermeasures&lt;sup&gt;&amp;#x03C0;&lt;/sup&gt;

Giani, Annarita; Bitar, Eilyan; García, María Teresa Iglesias; McQueen, Miles; Khargonekar, Pramod P.; Poolla, Kameshwar

doi:10.1109/smartgridcomm.2011.6102324

Cited by 115 publications

(100 citation statements)

References 21 publications

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“…The observation was made using a linearized model of the SE, but it was shown later on a SCADA/EMS testbed that stealth attacks are also possible under a non-linear model [4]. Since then the security of standalone SE has received much attention [3], [4], [5], [6], [7], [8], [9], [10]. Various schemes were proposed to mitigate stealth attacks, through individual data protection [5], through changes to the BDD algorithm [6], and through the protection of the SCADA infrastructure [7], [8].…”

Section: Related Workmentioning

confidence: 99%

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Security of Fully Distributed Power System State Estimation: Detection and Mitigation of Data Integrity Attacks

Vuković

Dán

2014

IEEE J. Select. Areas Commun.

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Abstract-State estimation plays an essential role in the monitoring and supervision of power systems. In today's power systems state estimation is typically done in a centralized or in a hierarchical way, but as power systems will be increasingly interconnected in the future smart grid, distributed state estimation will become an important alternative to centralized and hierarchical solutions. As the future smart grid may rely on distributed state estimation, it is essential to understand the potential vulnerabilities that distributed state estimation may have. In this paper, we show that an attacker that compromises the communication infrastructure of a single control center in an interconnected power system can successfully perform a denial of service attack against state-of-the-art distributed state estimation, and consequently it can blind the system operators of every region. As a solution to mitigate such a denial of service attack, we propose a fully distributed algorithm for attack detection. Furthermore, we propose a fully distributed algorithm that identifies the most likely attack location based on the individual regions' beliefs about the attack location, isolates the identified region, and then reruns the distributed state estimation. We validate the proposed algorithms on the IEEE 118 bus benchmark power system.

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Section: Related Workmentioning

confidence: 99%

“…The importance of SE has made its security a major concern, and therefore the vulnerability of standalone SEs to so called stealth attacks has been widely studied [3], [4], [5], [6], [7], [8], [9], [10]. Stealth attacks are false data injection attacks O.…”

Section: Introductionmentioning

confidence: 99%

Security of Fully Distributed Power System State Estimation: Detection and Mitigation of Data Integrity Attacks

Vuković

Dán

2014

IEEE J. Select. Areas Commun.

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“…As a consequence, unobservable attacks can cause significant errors in state estimation. In [13], we address sparse unobservable attacks which involve the compromise of a modest number of meters. Specifically, we offer efficient algorithms to find all unobservable attacks involving the compromise of exactly two power injection meters and an arbitrary number of power meters on lines.…”

Section: Unobservable Attacksmentioning

confidence: 99%

“…Specifically, we offer efficient algorithms to find all unobservable attacks involving the compromise of exactly two power injection meters and an arbitrary number of power meters on lines. Applying these algorithms to a synthetic 2383 bus power system, we identify 685 possible unobservable attacks that involve the compromise of 4 or fewer meters [13]. Other examples produce similar statistics.…”

Section: Unobservable Attacksmentioning

confidence: 99%

“…Known secure PMU placement problems have been studied by Bobba et al [16] who have investigated heuristic algorithms for mitigation of unobservable data integrity attacks. In [13] we have developed a method to resist such attacks while maintaining the robustness and reliability of the system. In our work [13], we have shown that p + 1 PMUs are sufficient to thwart a collection of p unobservable attacks and we offer an algorithm to determine their placement.…”

Section: Unobservable Attacksmentioning

confidence: 99%

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Metrics for assessment of smart grid data integrity attacks

Giani

Bent

Hinrichs

et al. 2012

2012 IEEE Power and Energy Society General Meeting

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Abstract-There is an emerging consensus that the nation's electricity grid is vulnerable to cyber attacks. This vulnerability arises from the increasing reliance on using remote measurements, transmitting them over legacy data networks to system operators who make critical decisions based on available data.Data integrity attacks are a class of cyber attacks that involve a compromise of information that is processed by the grid operator. This information can include meter readings of injected power at remote generators, power flows on transmission lines, and relay states. These data integrity attacks have consequences only when the system operator responds to compromised data by redispatching generation under normal or contingency protocols. These consequences include (a) financial losses from sub-optimal economic dispatch to service loads, (b) robustness/resiliency losses from placing the grid at operating points that are at greater risk from contingencies, and (c) systemic losses resulting from cascading failures induced by poor operational choices. This paper is focussed on understanding the connections between grid operational procedures and cyber attacks. We first offer an example to illustrate how data integrity attacks can cause economic and physical damage by misleading operators into taking inappropriate decisions. We then focus on unobservable data integrity attacks involving power meter data. These are coordinated attacks where the compromised data is consistent with the physics of power flow, and is therefore passed by any bad data detection algorithm. We develop metrics to assess the economic impact of these attacks under operator re-dispatch decisions using optimal power flow methods. These metrics can be used to prioritize the adoption of appropriate countermeasures including PMU placement, encryption, hardware upgrades, and advanced detection algorithms.

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Cyber Security of Smart Meters

Sánchez

Aung³

et al. 2016

Smart Grid Handbook

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The recently emerging advanced metering infrastructure (AMI) is envisioned to be one of the most prominent features of the smart grid. Security, especially authentication, is crucial for the success of large‐scale AMI deployment. Unfortunately, authentication schemes relying on per‐packet signature and per‐signature verification introduce heavy cost for computation and communication. Due to resource constraints, smart meter authentication requirements cannot be satisfied by this scheme. In this chapter, a new authentication architecture for AMI is described to validate the delay‐tolerant metering data. In this chapter, not only a set of efficient authentication schemes, but more importantly, their corresponding fault diagnosis algorithms will be recited. The authentication scheme incurs substantially lighter overheads than those by the existing schemes, while it can effectively address the formidable authentication challenges in AMI.

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Smart grid data integrity attacks: characterizations and countermeasures<sup>π</sup>

Cited by 115 publications

References 21 publications

Security of Fully Distributed Power System State Estimation: Detection and Mitigation of Data Integrity Attacks

Security of Fully Distributed Power System State Estimation: Detection and Mitigation of Data Integrity Attacks

Metrics for assessment of smart grid data integrity attacks

Cyber Security of Smart Meters

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