ABSTRACT
This chapter summarizes the contemporary challenges of cybersecurity and describes the applications of reinforcement learning on cybersecurity protection. Dynamic scheduling to manage cybersecurity analysts to minimize risk is a critical infrastructure problem that poses several operational challenges and garners importance at the level of national security. In addition to the lack of end-to-end solutions to the traditional cyber-security problems, new cybersecurity threats are emerging from the use of the advanced technology and the change of people’s daily behavior and the surroundings. The chapter presents a few examples of using reinforcement learning to resolve the emerging cybersecurity threats, which cannot be directly handled by the traditional anti-attack technologies. These examples are the representations of applications of significant advanced technologies, including mobile crowdsensing, cognitive radio network and edge computing. Mobile edge caching reduces the duplicated transmissions and backhaul traffic, improves the communication efficiency, and provides quality of services for caching users.
