Enhancing IoT Security Through Anomaly Detection and Intrusion Prevention in Cyber-Physical System

DOI

10.2991/978-94-6463-471-6_130How to use a DOI?

Keywords

Cybersecurity; Internet of Things; intrusion detection system (IDS); anomaly detection; security attacks; deep learning

Abstract

Cyber-attacks on cyber-physical systems can lead to severe consequences, jeopardizing the integrity, availability, and functionality of interconnected physical and digital components. Implications may include disruption of critical services, compromised safety, and potential economic losses. Existing deep learning models, such as CNN and RBM, exhibit low accuracy in detecting cyber-attacks on cyber-physical systems. The ineffectiveness of these models contributes to the inaccurate identification of attack patterns by intrusion detection systems (IDS). The inadequacy of current deep learning (DL) models translates into a reduced accuracy of intrusion detection systems. This deficiency hampers our ability to discern and respond to evolving cyber threats effectively. In response to the limitations of current models, a novel approach is introduced, leveraging a CNN + LSTM deep learning model. This model is applied comprehensively across datasets. The objective is to enhance accuracy, address previous detection model shortcomings, and provide a more robust defense against cyber-physical system attacks.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - R. Tamilkodi
AU  - N. Madhuri
AU  - N. Pavansai
AU  - D. Madhavi Sai Kasiratnam
AU  - K. Sri Manikanta Karthik
AU  - K. Venkata Naga Kiran
PY  - 2024
DA  - 2024/07/30
TI  - Enhancing IoT Security Through Anomaly Detection and Intrusion Prevention in Cyber-Physical System
BT  - Proceedings of the International Conference on Computational Innovations and Emerging Trends (ICCIET- 2024)
PB  - Atlantis Press
SP  - 1353
EP  - 1360
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-471-6_130
DO  - 10.2991/978-94-6463-471-6_130
ID  - Tamilkodi2024
ER  -