Requirements and specifications for adaptive security: concepts and analysis

In an adaptive security-critical system, security mechanisms change according to the type of threat posed by the environment. Specifying the behavior of these systems is diicult because conditions of the environment are diicult to describe until the system has been deployed and used for a length of time. This paper deines the problem of adaptation in security-critical systems, and outlines the RELAIS approach for expressing requirements and specifying the behavior in a way that helps identify the need for adaptation, and the appropriate adaptation behavior at runtime. The paper introduces the notion of adaptation via input approximation and proposes statistical machine learning techniques for realizing it. The approach is illustrated with a running example and is applied to a realistic security example from a cloud-based ile-sharing application. Bayesian classiication and logistic regression methods are used to implement adaptive speciications and these methods ofer diferent levels of adaptive security and usability in the ile-sharing application