IoT Network based Cyber Attack Mitigation in Digital Twin with Multi Level Key Management Using Enhanced KNN Model

Authors

  • Valluri. Padmapriya Research Scholar, Department of Computer Science-GITAM School of Science, GITAM Deemed to be University Visakhapatnam, Andhra Pradesh, India, Assistant Professor, Bhavan’s Vivekananda College, Secunderabad, Telangana, India
  • Muktevi Srivenkatesh Associate Professor, Department of Computer Science-GITAM School of Science, GITAM Deemed to be University Visakhapatnam, Andhra Pradesh, India

Keywords:

Internet of Things, Digital Twins, Cyber Physical Systems, Cryptography, Network Attacks, Key Management, Virtual Object, K Nearest Neighbor, Authentication, Security

Abstract

Internet of Things (IoT) technology have already been ingrained in many aspects of daily life, including public health, smart vehicles, smart grids, smart cities, smart manufacturing, and smart homes, with the number of Internet-connected devices estimated to reach about 30 billion by 2030. As a result, businesses began adopting and refining Digital Twin (DT) solutions. There are many security threats that will affect DTs despite their usefulness in enabling IoT systems. IoT devices with limited resources are more vulnerable to brute-force attacks, which can then be used as part of a botnet to launch cyber attacks. The increased likelihood of a large-scale cyber attack is compounded by the difficulty in preventing the transmission of malicious scripts to other devices while the botnet is still forming. Knowledge-driven open-source digital twin technologies of industrial control systems are selected after careful consideration of their implementation details. This digital twin is used by the cyber security analysis method to simulate various process-aware attack scenarios and produce a training dataset that reflects the process's measurements during both normal and attack operations. In a perfect world, Digital Twins would each have their own cryptographic identity separate from the host system to avoid attacks. In the actual world of industry, digital twins often operate in shady settings. Systems that mimic a significant part of the functionality of the device being twined fall into this category, but analytical methods also play a role. If an attacker wants to compromise the system's functioning including the Digital Twin, they need to have a thorough understanding of the target system. The suggested architecture also incorporates a cyber attack detection system that uses machine learning model. Critical systems benefit greatly from having a digital twin. However, digital twins also have applications in cyber security and safety. Cryptography enabled Multi Level Key Management using Enhanced K-Nearest Neighbor (CMLKM-EKNN) model that generates a key set in the IoT network for making strong authentication is proposed in this research. The proposed model key set contains key pairs that can be used for only one time to avoid attackers to reuse the keys for attacking the network. The EKNN model identifies the neighbor nodes, perform analysis and allocate weights to the features for attack detection in the network. A digital twin-based paradigm to aid in improving the cyber security of Cyber Physical Systems (CPSs) is proposed. Based on the strategy, the digital twin system can secure the CPSs. The proposed model when compared to the traditional model provides better security levels in the IoT Network.

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Published

02.02.2024

How to Cite

Padmapriya, V., & Srivenkatesh, M. . (2024). IoT Network based Cyber Attack Mitigation in Digital Twin with Multi Level Key Management Using Enhanced KNN Model . International Journal of Intelligent Systems and Applications in Engineering, 12(14s), 49–62. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4635

Issue

Vol. 12 No. 14s (2024)

Section

Research Article

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