How cyber-attacks in Ukraine show the vulnerability of the U.S. power grid

Sullivan, Julia E.; Kamensky, Dmitriy

doi:10.1016/j.tej.2017.02.006

Cited by 153 publications

(60 citation statements)

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“…Owing to the key role of substations in power systems, they have been a popular target for attackers to cause widespread blackouts [6], [39]. New technologies including microprocessor-based intelligent electronic devices (IEDs) and standardized networking protocols (e.g., TCP/IP) over wide area networks (WANs) are widely adopted in the substations.…”

Section: A Power Grid Overviewmentioning

confidence: 99%

RFDIDS: Radio Frequency-based Distributed Intrusion Detection System for the Power Grid

Shekari

Bayens

Cohen³

et al. 2019

Proceedings 2019 Network and Distributed System Security Symposium

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Recently, the number of cyber threats on power systems has increased at an unprecedented rate. For instance, the widespread blackout in Ukrainian power grid on December 2015 was a wakeup call that modern power systems have numerous vulnerabilities, especially in power substations which form the backbone of electricity networks. There have been significant efforts among researchers to develop effective intrusion detection systems (IDSs) in order to prevent such attacks or at least reduce their damaging consequences. However, all of the existing techniques require some level of trust from components on the supervisory control and data acquisition (SCADA) network; hence, they are still vulnerable to sophisticated attacks that can compromise the SCADA system completely. This paper presents a radio frequency-based distributed intrusion detection system (RFDIDS) which remains reliable even when the entire SCADA system is considered untrusted. The proposed system uses radio frequency (RF) emissions to monitor the power grid substation activities. Indeed, it utilizes a radio receiver as a diagnostic tool to provide air-gapped, independent, and verifiable information about the radio emissions from substation components, particularly at low frequencies (LF, 0.05−50 kHz, or >20 µs period). The simulation and experimental results verified that four types of diagnostic information can be extracted from radio emissions of power system substation circuits: i) harmonic content of the circuit current, ii) fundamental frequency of the circuit current, iii) impulsive signals from rapid circuit current changes, and iv) sferics from global lightning strokes. Each or a combination of the first three diagnostics can be effectively leveraged to directly detect specific types of power grid attacks. Meanwhile, the last diagnostic is utilized to check the integrity of the receiver's signal as it is encoded with the quasi-random distribution of the global lightning strokes. The simulation and real-world experimental results verified the effectiveness of RFDIDS in protecting the power grid against sophisticated attacks.

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Section: A Power Grid Overviewmentioning

confidence: 99%

RFDIDS: Radio Frequency-based Distributed Intrusion Detection System for the Power Grid

Shekari

Bayens

Cohen³

et al. 2019

Proceedings 2019 Network and Distributed System Security Symposium

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“…The first step consists of creating a correlated random time series according to (1). Randomness is introduced by using the variable ( ) , which is modeled as a Gaussian random number with a mean equal to zero and standard deviation equal to √1 − (Ø ) 2 . The second step consists of normalising the daily profile of Figure 2.…”

Section: Microgrid Simulation and Modellingmentioning

confidence: 99%

“…Similar to other industrial infrastructures, an intelligent system is exposed to risks from the interaction between the power system and the communication infrastructure (CI), as well as natural phenomena [1]. A representative example is the December 2015 cyber-attack in Ukraine, where a six-hour blackout affected hundreds of thousands of consumers in Kiev [2].…”

Section: Introductionmentioning

confidence: 99%

Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm

2019

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This work presents a management strategy for microgrid (MG) operation. Photovoltaic (PV) and wind generators, as well as storage systems and conventional units, are distributed over a wide geographical area, forming a distributed energy system, which is coordinated to face any contingency of the utility company by means of its isolated operation. The management strategy divides the system into three main layers: renewable generation, storage devices, and conventional units. Interactions between devices of the same layer are determined by solving an economic dispatch problem (EDP) in a distributed manner using a consensus algorithm (CA), and interactions between layers are determined by means of a load following strategy. In this way, the complex behaviour of PV and wind generation, the battery storage system, and conventional units has been effectively combined with CA to solve EDP in a distributed manner. MG performance and its vulnerability are deeply analysed by means of an illustrative case study. From the observed results, vulnerability under extreme conditions could be reduced up to approximately 30% by coupling distributed renewable generation and storage capacity with an energy system based on conventional generation.

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“…Additionally, the emergence of malicious malware such as Triton have testified to the capability of cyber attackers for harming the power systems. Furthermore, recent cyber security studies have called into question the capability of U.S.'s power grid for withstanding a major cyber attack [2][3][4]. In response to the concerns outlined above, a large body of research work has focused on studying cyber attack detection and prevention in power grids [5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20].…”

Section: Introductionmentioning

confidence: 99%

Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems

Yankson

Ghamkhari

2019

Future Internet

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The automatic generation control mechanism in power generators comes into operation whenever an over-supply or under-supply of energy occurs in the power grid. It has been shown that the automatic generation control mechanism is highly vulnerable to load altering attacks. In this type of attack, the power consumption of multiple electric loads in power distribution systems is remotely altered by cyber attackers in such a way that the automatic generation control mechanism is disrupted and is hindered from performing its pivotal role. The existing literature on load altering attacks has studied implementation, detection, and location identification of these attacks. However, no prior work has ever studied design of an attack-thwarting system that can counter load altering attacks, once they are detected in the power grid. This paper addresses the above shortcoming by proposing an attack-thwarting system for countering load altering attacks. The proposed system is based on provoking real-time adjustment in power consumption of the flexible loads in response to the frequency disturbances caused by the load altering attacks. To make the adjustments in-proportion to the frequency disturbances, the proposed attack-thwarting system uses a transactive energy framework to establish a coordination between the flexible loads and the power grid operator.

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How cyber-attacks in Ukraine show the vulnerability of the U.S. power grid

Cited by 153 publications

References 0 publications

RFDIDS: Radio Frequency-based Distributed Intrusion Detection System for the Power Grid

RFDIDS: Radio Frequency-based Distributed Intrusion Detection System for the Power Grid

Mitigating Energy System Vulnerability by Implementing a Microgrid with a Distributed Management Algorithm

Transactive Energy to Thwart Load Altering Attacks on Power Distribution Systems

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