A Multi-Agent System for Addressing Cybersecurity Issues in Social Networks

The constant interaction of individuals on social networks and its implications in their lives, which affects decision-making and can even impact their mental and physical health, sparks interest in studying these environments from different perspectives. Of particular interest is the case of cyberattacks on these platforms, which includes not only low-level hacking activity but also other events like cyberbullying, grooming, and hate speech, among others. In this paper, we investigate the design and implementation challenges faced in the deployment of a multi-agent system that operates in social network platforms to prevent or mitigate cyberattacks through the processing of streaming information using belief revision operations. We instantiate the multi-agent system using the recently-proposed HEIST application framework, which guides the implementation of hybrid socio-technical systems with a focus on explainability, and discuss the main challenges in this process. We propose two possible approaches to building new knowledge dynamics operators: a cautious operator and a credulous operator, and evaluate the implications and challenges in each case. In this preliminary work, we adopt a non-technical approach, focusing on building a roadmap of the problems that need to be solved in order to develop a concrete solution, which is outside the scope of this paper. We conclude by suggesting the first steps towards achieving the objective.