Learning from mutants: Using code mutation to learn and monitor invariants of a cyber-physical system

• Main Authors: CHEN, Yuqi, POSKITT, Christopher M., SUN, Jun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: anomaly detection; attacks; attestation; cyber physical systems; invariants; machine learning; mutation testing; system modelling; water treatment systems; Information Security; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/4906; https://ink.library.smu.edu.sg/context/sis_research/article/5909/viewcontent/Chen_Poskitt_Sun.SP.2018.pdf
• Institution: Singapore Management University

Cyber-physical systems (CPS) consist of sensors, actuators, and controllers all communicating over a network; if any subset becomes compromised, an attacker could cause significant damage. With access to data logs and a model of the CPS, the physical effects of an attack could potentially be detecte...