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Defending unknown attacks on cyber-physical systems by semi-supervised approach and available unlabeled data
journal contribution
posted on 2017-02-10, 00:00 authored by M D Huda, S Miah, M M Hasaan, R Islam, John YearwoodJohn Yearwood, M Alrubaian, A AlmogrenCyber-physical systems (CPS) are used increasingly in modern industrial systems. These systems currently encounter a significant threat of malicious activities created by malicious software intent on exploiting the fact that the software of such industrial systems is integrated with hardware and network systems. Malicious codes dynamically and continuously change their internal structure and attack patterns using obfuscation techniques, such as polymorphism and metamorphism, in order to bypass and hide from conventional malware detection engines. This requires continuously updating the database of the malware detection engine, which requires periodic effort from manual experts. This could limit the real-time protection of CPS. In addition, this also makes preserving the availability and integrity of the services provided by CPS against malicious code challenging because there is a demand for the development of specialized malware detection techniques for CPS.
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Journal
Information sciencesVolume
379Pagination
211 - 228Publisher
ElsevierLocation
Amsterdam, The NetherlandsPublisher DOI
ISSN
0020-0255eISSN
1872-6291Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2016, ElsevierUsage metrics
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