Biblio
Filters: Keyword is bad data injection [Clear All Filters]
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2019. A Survey of Attack Models for Cyber-Physical Security Assessment in Electricity Grid. 2019 IFIP/IEEE 27th International Conference on Very Large Scale Integration (VLSI-SoC). :242–243.
This paper surveys some prior work regarding attack models in a cyber-physical system and discusses the potential benefits. For comparison, the full paper will model a bad data injection attack scenario in power grid using the surveyed prior work.
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2019. A Hybrid Attack Model for Cyber-Physical Security Assessment in Electricity Grid. 2019 IEEE Texas Power and Energy Conference (TPEC). :1–6.
A detailed model of an attack on the power grid involves both a preparation stage as well as an execution stage of the attack. This paper introduces a novel Hybrid Attack Model (HAM) that combines Probabilistic Learning Attacker, Dynamic Defender (PLADD) model and a Markov Chain model to simulate the planning and execution stages of a bad data injection attack in power grid. We discuss the advantages and limitations of the prior work models and of our proposed Hybrid Attack Model and show that HAM is more effective compared to individual PLADD or Markov Chain models.
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2019. An Investigation on Detecting Bad Data Injection Attack in Smart Grid. 2019 International Conference on Computer and Information Sciences (ICCIS). :1–4.
Security and consistency of smart grids is one of the main issues in the design and maintenance of highly controlled and monitored new power grids. Bad data injection attack could lead to disasters such as power system outage, or huge economical losses. In many attack scenarios, the attacker can come up with new attack strategies that couldn't be detected by the traditional bad data detection methods. Adaptive Partitioning State Estimation (APSE) method [3] has been proposed recently to combat such attacks. In this work, we evaluate and compare with a traditional method. The main idea of APSE is to increase the sensitivity of the chi-square test by partitioning the large grids into small ones and apply the test on each partition individually and repeat this procedure until the faulty node is located. Our simulation findings using MATPOWER program show that the method is not consistent where it is sensitive the systems size and the location of faulty nodes as well.