Intelligent Solutions for Attack Mitigation in Zero-Trust Environments

Abstract

Many of today’s smart devices are rushed to market with little consideration for basic security and privacy protection, making them easy targets for various attacks. Therefore, IoT will benefit from adapting a zero-trust networking model which requires strict identity verification for every person and device trying to access resources on a private network, regardless of whether they are located within or outside of the network perimeter. Implementing such model can, however, become challenging, as the access policies have to be updated dynamically in the context of constantly changing network environment. In this research project, we are aiming to implement a prototype of intelligent defense framework relying on advanced technologies that have recently emerged in the area of software-defined networking and network function virtualization. The intelligent core of the system proposed is planned to employ several reinforcement machine learning agents which process current network state and mitigate both external attacker intrusions and stealthy advanced persistent threats acting from inside of the network environment.