From the point of view of a user, a security mechanism for a computer should protect it from the particular kind of attacks it is designed for, while influencing the performance of the computer for the user's applications as little as possible. In this paper, we present an evolutionary learning approach for exploratory testing of the performance consequences of a security mechanism on the user's usage profile, i.e. the applications the user is using.
By learning application interaction sequences with performances that are the most negatively influenced by the installation of a security mechanism, a user can evaluate if the performance losses are acceptable and by applying our approach to several mechanisms with comparable protection, a user can make an informed decision which mechanism is better for him/her. As proof-of-concept, we used our approach to explore anti-virus security mechanisms operating in a Windows XP environment. Our experiments show that different usage profiles are indeed better served by different security mechanism.
Generated: 24/9/19