Anomaly Detection in ICS based on Data-history Analysis

Hartmann, Laura; Wendzel, Steffen

doi:10.1145/3424954.3424963

Cited by 1 publication

(1 citation statement)

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“…It attacked more than 230,000 computers in over 150 countries and organizations, ranging from the UK National Health Service, the Bank of China, the Russian Interior Ministry, to FedEx [10]. Moreover, some viruses have been developed to launch advanced persistent threats (APTs) on industrial control systems, such as Stuxnet, Industroyer, and Triton [11,12]. In this context, it is extremely important to understand the propagation behavior of malware and then propose efficient control strategies to prevent its spread.…”

Section: Introductionmentioning

confidence: 99%

A Malware Propagation Model Considering Conformity Psychology in Social Networks

Zhu

Liu

Luo

et al. 2022

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At present, malware is still a major security threat to computer networks. However, only a fraction of users with some security consciousness take security measures to protect computers on their own initiative, and others who know the current situation through social networks usually follow suit. This phenomenon is referred to as conformity psychology. It is obvious that more users will take countermeasures to prevent computers from being infected if the malware spreads to a certain extent. This paper proposes a deterministic nonlinear SEIQR propagation model to investigate the impact of conformity psychology on malware propagation. Both the local and global stabilities of malware-free equilibrium are proven while the existence and local stability of endemic equilibrium is proven by using the central manifold theory. Additionally, some numerical examples and simulation experiments based on two network datasets are performed to verify the theoretical analysis results. Finally, the sensitivity analysis of system parameters is carried out.

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Section: Introductionmentioning

confidence: 99%