Towards in-situ Psychological Profiling of Cybercriminals Using Dynamically Generated Deception Environments
<|reference_start|>Towards in-situ Psychological Profiling of Cybercriminals Using Dynamically Generated Deception Environments: Cybercrime is estimated to cost the global economy almost \$10 trillion annually and with businesses and governments reporting an ever-increasing number of successful cyber-attacks there is a growing demand to rethink the strategy towards cyber security. The traditional, perimeter security approach to cyber defence has so far proved inadequate to combat the growing threat of cybercrime. Cyber deception offers a promising alternative by creating a dynamic defence environment. Deceptive techniques aim to mislead attackers, diverting them from critical assets whilst simultaneously gathering cyber threat intelligence on the threat actor. This article presents a proof-of-concept (POC) cyber deception system that has been developed to capture the profile of an attacker in-situ, during a simulated cyber-attack in real time. By dynamically and autonomously generating deception material based on the observed attacker behaviour and analysing how the attacker interacts with the deception material, the system outputs a prediction on the attacker's motive. The article also explores how this POC can be expanded to infer other features of the attacker's profile such as psychological characteristics. By dynamically and autonomously generating deception material based on observed attacker behaviour and analysing how the attacker interacts with the deception material, the system outputs a prediciton on the attacker's motive. The article also explores how this POC can be expanded to infer other features of the attacker's profile such as psychological characteristics.<|reference_end|>
@article{quibell2024towards,
    title={Towards in-situ Psychological Profiling of Cybercriminals Using
  Dynamically Generated Deception Environments},
    author={Jacob Quibell},
    journal={arXiv preprint arXiv:2405.11497},
    year={2024},
    archivePrefix={arXiv},
    eprint={2405.11497},
    primaryClass={cs.CR}
}