A Systematic Survey of Self-Protecting Software Systems

  • Authors:
  • Eric Yuan;Naeem Esfahani;Sam Malek

  • Affiliations:
  • George Mason University;George Mason University;George Mason University

  • Venue:
  • ACM Transactions on Autonomous and Adaptive Systems (TAAS) - Special Section on Best Papers from SEAMS 2012
  • Year:
  • 2014

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Abstract

Self-protecting software systems are a class of autonomic systems capable of detecting and mitigating security threats at runtime. They are growing in importance, as the stovepipe static methods of securing software systems have been shown to be inadequate for the challenges posed by modern software systems. Self-protection, like other self-* properties, allows the system to adapt to the changing environment through autonomic means without much human intervention, and can thereby be responsive, agile, and cost effective. While existing research has made significant progress towards autonomic and adaptive security, gaps and challenges remain. This article presents a significant extension of our preliminary study in this area. In particular, unlike our preliminary study, here we have followed a systematic literature review process, which has broadened the scope of our study and strengthened the validity of our conclusions. By proposing and applying a comprehensive taxonomy to classify and characterize the state-of-the-art research in this area, we have identified key patterns, trends and challenges in the existing approaches, which reveals a number of opportunities that will shape the focus of future research efforts.