Achievement: A team of Oak Ridge National Laboratory (ORNL) scientists involved in research topics of cybersecurity, statistical approaches, control systems, and dynamical models, reported a basic approach to security of physical systems that are interfaced with IT systems. The so-called cyber physical security explores ways to secure industrial and infrastructural systems against cyber-attacks and tampering/malicious activities that may result in the malfunction of a system such as a 3D printer or a DNA synthesis machine. These systems are increasingly vulnerable to software and hardware attacks, or the so-called side-channel attacks, which could result in catastrophic outcome, e.g., a defect planted in a critical component or an incorrect sequence in a DNA molecule.
Significance and Impact: Researchers employed a Bayesian statistical model to make inferences on the behavior of a physical system. In their preliminary work, they modeled the physical system as a control system based on a harmonic oscillator. However, more advanced systems can be built upon the reported results, if high-performance computing can be employed. With sufficient processing power, the speed by which the Bayesian algorithm can generate an inference of the state of the system can be improved and more elaborate dynamical systems can be modeled. The needed processing power can be provided from yet another research front, namely that of edge computing. A dedicated edge computing processor can be tasked to crunch the numbers in the various steps of the Bayesian solution.
Research Details
- Model the cyber physical system using e.g., multidimensional partial differential equation systems
- Compute system dynamics identification and compute a linear or nonlinear transfer function for the model
- Invoke the transfer function as a prior for the Bayesian algorithm
- Execute Bayesian algorithm
Facility: Both DNA synthesis machine and the 3D printer were acquired by ORNL using funds from LDRD funds.
Sponsor/Funding: ORNL LDRD Project 9820
PI and affiliation: Joel Dawson, Cyber Security Researcher, Energy and Control Systems Security Group, Oak Ridge National Laboratory
Team: Joseph Lukens, Ali Passian, Srikanth Yoginath, Kody Law, and Joel Dawson
Citation and DOI: Lukens, Joseph M., Ali Passian, Srikanth Yoginath, Kody J. H. Law, and Joel A. Dawson. 2022. "Bayesian Estimation of Oscillator Parameters: Toward Anomaly Detection and Cyber-Physical System Security" Sensors 22, no. 16: 6112. https://doi.org/10.3390/s22166112
Summary: A basic concept was presented for countering attacks that can impact the performance of industrial systems. The simplicity of the system poses no limitation on the potential of the concept to be extended to more elaborate dynamical systems such as those formulated as a multi-parameter multivariate system. As a use-case study, we studied the response of a test actuator in the form of a mechanical rotor. The frequency of the system was inferred by the application of the presented Bayesian method.
