MENTOR: The Design and Evaluation of a Protection Services Recommender System

Cyberattacks are the cause of several damages on governments and companies in the last years. Such damage includes not only leaks of sensitive information, but also economic loss due to downtime of services. The security market size worth billions of dollars, which represents investments to acquire protection services and training response teams to operate such services, determines a considerable part of the investment in technologies around the world. Although a vast number of protection services are available, it is neither trivial for network operators nor end-users to choose one of them in order to prevent or mitigate an imminent attack. As the next-generation cybersecurity solutions are on the horizon, systems that simplify their adoption are still required in support of security management tasks. Thus, this paper introduces MENTOR, a support tool for cyber-security, focusing on the recommendation of protection services. MENTOR is able to (${a}$) to deal with different demands from the user and (${b}$) to recommend the adequate protection service in order to provide a proper level of cybersecurity in different scenarios. Four similarity measurements are implemented in order to prove the feasibility of the MENTOR’${s}$ engine. An evaluation determines the performance and accuracy of each measurement used during the recommendation process.