Offensive Machine Learning Methods and the Cyber Kill Chain
Turtiainen, H., Costin, A., Polyakov, A., & Hämäläinen, T. (2023). Offensive Machine Learning Methods and the Cyber Kill Chain. In T. Sipola, T. Kokkonen, & M. Karjalainen (Eds.), Artificial Intelligence and Cybersecurity : Theory and Applications (pp. 125-145). Springer. https://doi.org/10.1007/978-3-031-15030-2_6
Date
2023Discipline
TekniikkaTietotekniikkaSecure Communications Engineering and Signal ProcessingEngineeringMathematical Information TechnologySecure Communications Engineering and Signal ProcessingCopyright
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
Cyberattacks are the “new normal” in the hyper-connected and all-digitized modern world, as breaches, denial-of-service, ransomware, and a myriad of other attacks occur every single day. As the attacks and breaches increase in complexity, diversity, and frequency, cybersecurity actors (both ethical and cybercrime) turn to automating these attacks in various ways and for a variety of reasons, including the development of effective and superior cybersecurity defenses. In this chapter, we address innovations in machine learning, deep learning, and artificial intelligence within the offensive cybersecurity fields. We structure this chapter inline with the Lockheed Martin’s Cyber Kill Chain taxonomy in order to cover adequate grounds on this broad topic, and occasionally refer to the more granular MITRE ATT&CK taxonomy whenever relevant.
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978-3-031-15029-6Is part of publication
Artificial Intelligence and Cybersecurity : Theory and ApplicationsKeywords
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https://converis.jyu.fi/converis/portal/detail/Publication/164482646
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