A review on security analysis of cyber physical systems using Machine learning

被引:23
|
作者
Ahmed Jamal A. [1 ]
Mustafa Majid A.-A. [1 ]
Konev A. [1 ]
Kosachenko T. [1 ]
Shelupanov A. [1 ]
机构
[1] Department of Complex Information Security of Computer Systems, Faculty of Security, Tomsk State University of Control Systems and Radioelectronics, Tomsk
来源
Materials Today: Proceedings | 2023年 / 80卷
关键词
Cyber security; Cyber threat intelligence; Intrusion detection; Machine learning;
D O I
10.1016/j.matpr.2021.06.320
中图分类号
学科分类号
摘要
The concept of Cyber Physical System (CPS) is widely used in different industries across the globe. In fact, it is the holistic approach towards dealing with cyber space and physical environments that do have inter-dependencies. In the existing systems, there was a separate approach for security of the two worlds (cyber and physical). However, it does not provide necessary security when security is employed independently. The research in this paper identifies the need for integrated security for CPS. Besides it throws light into different security challenges associated with CPS and the countermeasures that existed based on machine learning and deep learning techniques that come under Artificial Intelligence (AI) and data science. From the review of literature, it is understood that data science perspective is suitable for protecting CPS with required adaptive strategy. This paper provides several useful insights related to security analysis of CPS using machine learning. It paves way for further investigation and realize a comprehensive security framework to protect CPS from internal and external cyber-attacks. © 2021
引用
收藏
页码:2302 / 2306
页数:4
相关论文
共 50 条
  • [1] Resilient Machine Learning for Networked Cyber Physical Systems: A Survey for Machine Learning Security to Securing Machine Learning for CPS
    Olowononi, Felix O.
    Rawat, Danda B.
    Liu, Chunmei
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2021, 23 (01): : 524 - 552
  • [2] A Systematic Analysis of Enhancing Cyber Security Using Deep Learning for Cyber Physical Systems
    Gaba, Shivani
    Budhiraja, Ishan
    Kumar, Vimal
    Martha, Sheshikala
    Khurmi, Jebreel
    Singh, Akansha
    Singh, Krishna Kant
    Askar, S. S.
    Abouhawwash, Mohamed
    IEEE ACCESS, 2024, 12 : 6017 - 6035
  • [3] Security Analysis of Cyber-Physical Systems Using Reinforcement Learning
    Ibrahim, Mariam
    Elhafiz, Ruba
    SENSORS, 2023, 23 (03)
  • [4] Machine Learning-Based Security Solutions for Critical Cyber-Physical Systems
    Raza, Asad
    Memon, Shahzad
    Nizamani, Muhammad Ali
    Shah, Mahmood Hussain
    2022 10TH INTERNATIONAL SYMPOSIUM ON DIGITAL FORENSICS AND SECURITY (ISDFS), 2022,
  • [5] A Review on Cyber Security Datasets for Machine Learning Algorithms
    Yavanoglu, Ozlem
    Aydos, Murat
    2017 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2017, : 2186 - 2193
  • [6] Machine learning and cyber security
    Karius, Sebastian
    Knoechel, Mandy
    Hesse, Sascha
    Reiprich, Tim
    IT-INFORMATION TECHNOLOGY, 2023, 65 (4-5): : 142 - 154
  • [7] Machine Learning for Threat Recognition in Critical Cyber-Physical Systems
    Perrone, Paola
    Flammini, Francesco
    Setola, Roberto
    PROCEEDINGS OF THE 2021 IEEE INTERNATIONAL CONFERENCE ON CYBER SECURITY AND RESILIENCE (IEEE CSR), 2021, : 298 - 303
  • [8] Security Engineering with Machine Learning for Adversarial Resiliency in Mobile Cyber Physical Systems
    Olowononi, Felix O.
    Rawat, Danda B.
    Garuba, Moses
    Kamhoua, Charles
    ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING FOR MULTI-DOMAIN OPERATIONS APPLICATIONS, 2019, 11006
  • [9] Security of Machine Learning-Based Anomaly Detection in Cyber Physical Systems
    Jadidi, Zahra
    Pal, Shantanu
    Nayak, Nithesh K.
    Selvakkumar, Arawinkumaar
    Chang, Chih-Chia
    Beheshti, Maedeh
    Jolfaei, Alireza
    2022 31ST INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATIONS AND NETWORKS (ICCCN 2022), 2022,
  • [10] Comparative Analysis of Cyber Security Approaches Using Machine Learning in Industry 4.0
    Cebeloglu, F. Sumeyye
    Karakose, Mehmet
    2020 6TH IEEE INTERNATIONAL SYMPOSIUM ON SYSTEMS ENGINEERING (IEEE ISSE 2020), 2020,