Code integrity attestation for PLCs using black box neural network predictions

• Main Authors: CHEN, Yuqi, POSKITT, Christopher M., SUN, Jun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2021
• Subjects: Cyber-physical systems; programmable logic controllers; attestation; code integrity checking; neural networks; adversarial attacks; OS and Networks; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/6583; https://ink.library.smu.edu.sg/context/sis_research/article/7586/viewcontent/plc_attestation_esecfse21.pdf
• Institution: Singapore Management University

Cyber-physical systems (CPSs) are widespread in critical domains, and significant damage can be caused if an attacker is able to modify the code of their programmable logic controllers (PLCs). Unfortunately, traditional techniques for attesting code integrity (i.e. verifying that it has not been mod...