A Novel Asset Authentication Scheme for Cyber Physical Systems

Abstract

Cyber physical assets are being widely deployed. An asset could be a device or object in Cyber physical system (CPS). Many of them are subjected to compromise due to insecure implementations and configuration. Existing authentication techniques are not effective in detecting compromised assets given the massive scale of deployment. In this paper, we present a system for detecting compromised CPS assets effectively. In contrast to prior work, we propose an asset authentication framework that uses device-specific and network information with weight vectors, called slanted fingerprints, to validate assets. In particular, we perform asset fingerprinting with environmental effects to detect the cyber-physical emulation attacks on authentication. The framework tracks the effect of changes in the physical environment on fingerprints and uses unique CPS environmental effects features to detect both cyber-physical emulation and advanced stealthy attacks.