scholarly journals Cyber Attack Prevention Based on Evolutionary Cybernetics Approach

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1931
Author(s):  
Dmitry Zegzhda ◽  
Daria Lavrova ◽  
Evgeny Pavlenko ◽  
Anna Shtyrkina
Keyword(s):  
Methodological Approach ◽  
Self Regulation ◽  
Evolutionary Model ◽  
Cyber Physical Systems ◽  
Cyber Attacks ◽  
Evolutionary Models ◽  
Cyber Attack ◽  
Discussion Section ◽  
Physical Systems ◽  
Security Incidents

The paper looks at the problem of cybersecurity in modern cyber–physical systems and proposes an evolutionary model approach to counteract cyber attacks by self-regulating the structure of the system, as well as several evolutionary indicators to assess the state of the system. The application of evolutionary models makes it possible to describe the regularities of systems behavior and their technical development, which is especially important regarding cyber attacks, which are the cause of a discontinuous evolution of complex systems. A practical example describes a system behavior during attacks and the self-regulation of its structure. The methodological approach consists of using evolutionary models to describe how modern cyber–physical systems can counteract cyber attacks and evolve, building on the experience of past security incidents. The main conclusions and recommendations are presented in the Discussion section, and they consist of the fact that using an evolutionary approach will not only increase the security of cyber–physical systems, but also define the principles of building systems that are resistant to cyber attacks.

Scalable Anomaly Detection and Isolation in Cyber-Physical Systems Using Bayesian Networks

2014 ◽  
Author(s):  
Sudha Krishnamurthy ◽  
Soumik Sarkar ◽  
Ashutosh Tewari
Keyword(s):  
Anomaly Detection ◽  
Bayesian Network ◽  
Cyber Physical Systems ◽  
Cyber Attacks ◽  
Cyber Attack ◽  
Scalable Algorithms ◽  
Commercial Building ◽  
Physical Systems ◽  
Temporal Correlations ◽  
The Impact

Anomalies in cyber-physical systems may arise due to malicious cyber attacks or operational faults in the physical devices. Accurately detecting the anomalies and isolating their root-causes is important for identifying appropriate reactive and preventive measures and building resilient cyber-physical systems. Anomaly detection and isolation in cyber-physical systems is challenging, because the impact of a cyber attack on the operation of a physical system may manifest itself only after some time. In this paper, we present a Bayesian network approach for learning the causal relations between cyber and physical variables as well as their temporal correlations from unlabeled data. We describe the data transformations that we performed to deal with the heterogeneous characteristics of the cyber and physical data, so that the integrated dataset can be used to learn the Bayesian network structure and parameters. We then present scalable algorithms to detect different anomalies and isolate their respective root-cause using a Bayesian network. We also present results from evaluating our algorithms on an unlabeled dataset consisting of anomalies due to cyber attacks and physical faults in a commercial building system.

Toward Detection and Attribution of Cyber-Attacks in IoT-enabled Cyber-physical Systems

2021 ◽  
pp. 1-1
Author(s):  
Amir Namavar Jahromi ◽  
Hadis Karimipour ◽  
Ali Dehghantanha ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Cyber Physical Systems ◽  
Cyber Attacks ◽  
Physical Systems ◽  
Detection And Attribution

scholarly journals Incidents Are Meant for Learning, Not Repeating: Sharing Knowledge About Security Incidents in Cyber-Physical Systems

2020 ◽  
pp. 1-1
Author(s):  
Faeq Alrimawi ◽  
Liliana Pasquale ◽  
Deepak Mehta ◽  
Nobukazu Yoshioka ◽  
Bashar Nuseibeh
Keyword(s):  
Cyber Physical Systems ◽  
Physical Systems ◽  
Security Incidents

Dual Redundant Cyber-Attack Tolerant Control Systems Strategy for Cyber-Physical Systems

2019 ◽  
Author(s):  
Marco A. Gamarra ◽  
Sachin Shetty ◽  
Oscar R. Gonzalez ◽  
Laurent Njilla ◽  
Marcus Pendleton ◽  
...  
Keyword(s):  
Control Systems ◽  
Cyber Physical Systems ◽  
Cyber Attack ◽  
Physical Systems

scholarly journals Nonfragile Integral-Based Event-Triggered Control of Uncertain Cyber-Physical Systems under Cyber‐Attacks

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-14 ◽  
Author(s):  
Shen Yan ◽  
Sing Kiong Nguang ◽  
Liruo Zhang
Keyword(s):  
Sufficient Conditions ◽  
Cyber Physical Systems ◽  
Cyber Attacks ◽  
Linear Matrix ◽  
Time Interval ◽  
System State ◽  
Network Resources ◽  
Physical Systems ◽  
Mean Square Stability ◽  
Event Triggered

This article studies the problem of nonfragile integral-based event-triggered control for uncertain cyber-physical systems under cyber-attacks. An integral-based event-triggered scheme is proposed to reduce the data transmissions and save the limited network resources. The triggering condition is related to the mean of system state over a finite time interval instead of instant system state. Random cyber-attacks in a communication channel are taken into account and described by a stochastic variable subject to Bernoulli distribution. A novel Lyapunov–Krasovskii functional based on Legendre polynomials is constructed, and the Bessel–Legendre inequality technique is employed to handle the integral term induced by the integral-based event-triggered scheme. Resorting to these treatments, sufficient conditions are established via a set of linear matrix inequalities to guarantee the asymptotic mean-square stability of the closed-loop system. Finally, a numerical example shows that the presented method is effective.

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