Deception for Cyber Defence: Challenges and Opportunities
This is an incremental vision paper that outlines opportunities for improving cyber defense through automated deception, primarily benefiting security professionals.
The paper addresses the challenge of high costs in manually generating realistic deception artifacts for cyber defense by proposing the use of machine learning for scalable, automated generation, though it does not provide specific results or numbers.
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.