Cyber Physical System for Distributed Network Using DoS Based Hierarchical Bayesian Network

doi:10.1007/s10723-023-09662-1

Cyber Physical System for Distributed Network Using DoS Based Hierarchical Bayesian Network

2023-05-22

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DOI：10.1007/s10723-023-09662-1

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The Cyber Physical System (CPS) is a prime target for cyber attacks due to its heterogeneity and connectivity with physical equipment. This paper proposes a model based on a Hierarchical Bayesian Network (HBN) to increase the CPS's attack detection ability. Denial of Service (DoS) attacks pose a significant threat to production line availability, business services, and human lives. Therefore, this paper focuses on detecting DoS attacks using the Bayesian network model, an efficient algorithm to detect faults in the networking system based on incomplete recognizing information. The standard Bayesian network model is hierarchically enhanced and optimized with a Bacterial Foraging Optimization (BFO) approach to improve the detection process. The developed, optimized model satisfies security, Quality of Service (QoS) requirements, and time consumption by reducing the constraints to obtain system reliability. The efficiency of the proposed model is evaluated using the NSL-KDD dataset and compared with existing approaches in terms of accuracy, precision, recall, F1-score, ROC, and RMSE. Compared to other existing systems, the proposed model achieves an accuracy of 98.4% in detecting DoS attacks with a reduced RMSE of 0.0617.

Keywords:

Cyber-physical system (CPS)

Bayesian network

Optimization

Bacterial foraging

distributed network

Denial of Service

Bird swarm optimization

Cyber Physical System for Distributed Network Using DoS Based Hierarchical Bayesian Network

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