@inproceedings{5c636d1c56154d339b08a90d8aaca2c0,
title = "Deception for Cyber Defence: Challenges and Opportunities",
abstract = "Deception is rapidly growing as an important tool for cyber defence, complementing existing perimeter security measures to rapidly detect breaches and data theft. One of the factors limiting the use of deception has been the cost of generating realistic artefacts by hand. Recent advances in Machine Learning have, however, created opportunities for scalable, automated generation of realistic deceptions. This vision paper describes the opportunities and challenges involved in developing models to mimic many common elements of the IT stack for deception effects.",
keywords = "cyber deception, generative modelling, simulation",
author = "David Liebowitz and Surya Nepal and Kristen Moore and Christopher, \{Cody J.\} and Kanhere, \{Salil S.\} and David Nguyen and Timmer, \{Roelien C.\} and Michael Longland and Keerth Rathakumar",
note = "Publisher Copyright: {\textcopyright} 2021 IEEE.; 3rd IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA 2021 ; Conference date: 13-12-2021 Through 15-12-2021",
year = "2021",
doi = "10.1109/TPSISA52974.2021.00020",
language = "English",
series = "IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "173--182",
booktitle = "Proceedings - 2021 3rd IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications, TPS-ISA 2021",
address = "United States",
}