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Data Poisoning Vulnerabilities Across Health Care Artificial Intelligence Architectures: Analytical Security Framework and Defense Strategies. [PDF]

J Med Internet Res
Abtahi F, Seoane F, Pau I, Vega-Barbas M.   +3 more
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Mathematical modeling of adaptive information security strategies using composite behavior models. [PDF]

Sci Rep
Nuaim AA, Nuaim AA, Nadeem M, Agrawal A.
europepmc   +1 more source

Optimized ensemble machine learning model for cyberattack classification in industrial IoT. [PDF]

Front Artif Intell
Alabdullah B, Sankaranarayanan S.
europepmc   +1 more source

D3O-IIoT: deep reinforcement learning-driven dynamic deception orchestration for industrial IoT security. [PDF]

Sci Rep
Wushishi U, Hussain A, Khalid MI, Hussain N, Jamjoom M, Ullah Z.   +5 more
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False-Data-Injection Attacks on Remote Distributed Consensus Estimation

IEEE Transactions on Cybernetics, 2022
This article studies a security issue in remote distributed consensus estimation where sensors transmit their measurements to remote estimators via a wireless communication network. The relative entropy is utilized as a stealthiness metric to detect whether the data transmitted through the wireless network are attacked.
Hao Liu, Ben Niu, Yuzhe Li
openaire   +2 more sources

Distributed filtering under false data injection attacks

Automatica, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Yang, Wen, Zhang, Yu, Chen, Guanrong, Yang, Chao, Shi, Ling   +4 more
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False Data Injection Attacks in Electricity Markets

2010 First IEEE International Conference on Smart Grid Communications, 2010
We present a potential class of cyber attack, named false data injection attack, against the state estimation in deregulated electricity markets. With the knowledge of the system configuration, we show that such attacks will circumvent the bad data measurement detection equipped in present SCADA systems, and lead to profitable financial misconduct such
Le Xie, Yilin Mo, Bruno Sinopoli
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Secure distributed estimation against false data injection attack

Information Sciences, 2020
Abstract With the development of wireless sensor networks, many distributed algorithms have been studied by researchers. This paper considers the situation of distributed estimation with false data injection (FDI) attack. Owing to the fact that Kullback-Leibler (KL) divergence is very effective to detect outliers caused by FDI attack, a distributed ...
Yi Hua, Feng Chen, Shuwei Deng, Shukai Duan, Lidan Wang   +4 more
openaire   +1 more source