Requirements and specifications for adaptive security: Concepts and analysis

Abstract

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 difficult because conditions of the environment are difficult to describe until the system has been deployed and used for a length of time. This paper defines 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 file-sharing application. Bayesian classification and logistic regression methods are used to implement adaptive specifications and these methods offer different levels of adaptive security and usability in the file-sharing application.