Communication security for smart grid distribution networks

Bou‐Harb, Elias; Fachkha, Claude; Pourzandi, Makan; Debbabi, Mourad; Assi, Chadi

doi:10.1109/mcom.2013.6400437

Cited by 185 publications

(98 citation statements)

References 8 publications

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“…The second type of availability attacks, RF jamming is an availability attack, which is characterized by interruption of the network's communication by interference utilizing radio signals for an undefined period of time [8]. Therefore, the simulation of RF jamming aims at the interruption of data transmission for different lengths of time.…”

Section: Cyber-attacksmentioning

confidence: 99%

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Cyber-Attacks on Smart Meters in Household Nanogrid: Modeling, Simulation and Analysis

Tellbach

2018

Energies

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Abstract:The subject of cyber-security and therefore cyber-attacks on smart grid (SG) has become subject of many publications in the last years, emphasizing its importance in research, as well as in practice. One especially vulnerable part of SG are smart meters (SMs). The major contribution of simulating a variety of cyber-attacks on SMs that have not been done in previous studies is the identification and quantification of the possible impacts on the security of SG. In this study, a simulation model of a nanogrid, including a complete household with an SM, was developed. Different cyber-attacks were injected into the SM to simulate their effects on household nanogrid. The analysis of the impacts of different cyber-attacks showed that the effects of cyber-attacks can be sorted into various categories. Integrity and confidentiality attacks cause monetary effects on the grid. While, availability attacks have monetary effects on the grid as well, they are mainly aimed at compromising the SM communication by either delaying or stopping it completely.

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Section: Cyber-attacksmentioning

confidence: 99%

“…Due to these weaknesses, SMs make SGs vulnerable to malicious attempts to obtain, alter, or even destroy any cyber/physical component or subsystem [8]. In summary, the higher the complexity of the SM and the more features and functions are realized and used, the more opportunities that attackers might have to conduct cyber-attacks on them.…”

Section: Introductionmentioning

confidence: 99%

Cyber-Attacks on Smart Meters in Household Nanogrid: Modeling, Simulation and Analysis

Tellbach

2018

Energies

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“…and M is the total number of particles, 1,2, ⋯ , . and N is particle dimension, is the inertia weight, , is constant negative acceleration, usually at the [0,4] between values, , is random number [0,1], is the speed of the particles at the k th iteration, is the location of the particles at the k th iteration,, is the location of the particle at the D individual extremum, is the most optimal fitness sorted according to the history, the stronger the wild goose individual extreme value, the speed of the particles in each dimension are confined within the scope of the , , and . , 0.1 0.2 When the geese fly in migration mainly rely on teamwork, in front of geese for flight, can only rely on their own experience in the back of the geese flying experience not only rely on themselves, also can be based on the experience of the in front of the wild goose to fly, and to adapt the current value as the weight value of the reference.…”

Section: Improved Particle Swarm Optimization Algorithmmentioning

confidence: 99%

Optimization method of power communication network based on improved particle swarm optimization

He¹,

Peng²,

Zhang³

et al. 2018

IOP Conf. Ser.: Earth Environ. Sci.

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“…The objective is to find an estimate x of x that is the best fit of the measurement z according to Equation (1). The problem is usually solved by the weighted least squares (WLS) algorithm [3].…”

Section: Sementioning

confidence: 99%

“…For this purpose many sensors are deployed across millions of buildings and streets. They are connected to the information network, raising the issue of how to protect the system against false data injection (FDI) attacks, which are launched by hijacking and tampering with communication, or illegal access and control of electrical devices [1]. Moreover, FDI attacks are quite attractive to hackers, since the data in smart grid can be easily monetized (e.g., hackers can manipulate their energy costs by modifying the smart meter readings).…”

Section: Introductionmentioning

confidence: 99%

Extended Distributed State Estimation: A Detection Method against Tolerable False Data Injection Attacks in Smart Grids

et al. 2014

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False data injection (FDI) is considered to be one of the most dangerous cyber-attacks in smart grids, as it may lead to energy theft from end users, false dispatch in the distribution process, and device breakdown during power generation. In this paper, a novel kind of FDI attack, named tolerable false data injection (TFDI), is constructed. Such attacks exploit the traditional detector's tolerance of observation errors to bypass the traditional bad data detection. Then, a method based on extended distributed state estimation (EDSE) is proposed to detect TFDI in smart grids. The smart grid is decomposed into several subsystems, exploiting graph partition algorithms. Each subsystem is extended outward to include the adjacent buses and tie lines, and generate the extended subsystem. The Chi-squares test is applied to detect the false data in each extended subsystem. Through decomposition, the false data stands out distinctively from normal observation errors and the detection sensitivity is increased. Extensive TFDI attack cases are simulated in the Institute of Electrical and Electronics Engineers (IEEE) 14-, 39-, 118-and 300-bus systems. Simulation results show that the detection precision of the EDSE-based method is much higher than that of the traditional method, while the proposed method significantly reduces the associated computational costs.

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Communication security for smart grid distribution networks

Cited by 185 publications

References 8 publications

Cyber-Attacks on Smart Meters in Household Nanogrid: Modeling, Simulation and Analysis

Cyber-Attacks on Smart Meters in Household Nanogrid: Modeling, Simulation and Analysis

Optimization method of power communication network based on improved particle swarm optimization

Extended Distributed State Estimation: A Detection Method against Tolerable False Data Injection Attacks in Smart Grids

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