USMD: UnSupervised Misbehaviour Detection for Multi-Sensor Data
Version 2 2024-06-05, 04:15Version 2 2024-06-05, 04:15
Version 1 2022-02-04, 08:20Version 1 2022-02-04, 08:20
journal contribution
posted on 2024-06-05, 04:15authored byA Alsaedi, Z Tari, R Mahmud, N Moustafa, AN Mahmood, Adnan AnwarAdnan Anwar
Cyber-Physical Systems (CPSs) enable Information Technology to be integrated with Operation Technology to efficiently monitor and manage the physical processes of various critical infrastructures. Recent incidents in cyber ecosystems have shown that CPSs are becoming increasingly vulnerable to complex attacks. These incidents often lead to sensing and actuation misbehaviour by illegal manipulations of data, which can severely impact the underlying physical processes of critical infrastructures. Current research acknowledges that IT-based security measures cannot entirely protect CPSs from such threats. Moreover, they are not designed to monitor the measurement level activities of physical processes, and they fail to mitigate blended cyberattacks, especially multi-stage and zero-day ones. This paper addresses these limitations by proposing a framework, named UnSupervised Misbehaviour Detection (USMD), comprising a deep neural network that learns about a systems expected behaviour from data-driven representations. USMD can identify in real-time the attacks on CPSs by using the long-short term memory and Attention method for multi-sensor data. The USMDs performance is evaluated on various known data sets (i.e., ToN IoT, SWaT,WADI and Gas pipeline datasets). The experimental results indicate that the superior performance of USMD compared with six state-of-the-art methods, which we implemented and extensively tested. USMD achieves F-scores of 0.9699 and 0.9702 on SWaT and WADI datasets, respectively.
History
Journal
IEEE Transactions on Dependable and Secure Computing
Pagination
1-16
Location
Piscataway, NJ
ISSN
1545-5971
eISSN
1941-0018
Language
English
Publication classification
C1 Refereed article in a scholarly journal
Publisher
Institute of Electrical and Electronics Engineers (IEEE)