Sensor Verification for Cyber-Physical Models of Power Systems

This project explores the ways that data from sensors in power systems can be authenticated by enhancing the security of power systems from a cyber-physical point of view. This is a continuation of the work for the NSF project “CPS: Synergy: Collaborative Research: Distributed Just-Ahead-Of-Time Verification of Cyber-Physical Critical Infrastructure.” Adversaries who gain access to a cyber-physical system can cause significant physical damage and financial loss by injecting false data into a sensor node. Identifying adversarial action in a system can mitigate unsafe actions made based off of bad data. The technique presented in this work combines topology analysis with real-time probing to create a measure of trustworthiness of sensors in a system. A previously developed tool called Cyber Physical Security Assessment (CyPSA) gives each node a topology vulnerability score based on the cyber accessibility and potential physical impact should it be compromised. We develop a real-time vulnerability score by simulating attack and non-attack scenarios with PowerWorld. The data from these simulations is processed in MATLAB. Results show improved attack detection over current methods. The measure of trustworthiness developed will improve attack detection in power systems, and it may be used to help prevent a system from entering an unstable state

Sensor Verification for Cyber-Physical Models of Power Systems

This project explores the ways that data from sensors in power systems can be authenticated by enhancing the security of power systems from a cyber-physical point of view. This is a continuation of the work for the NSF project “CPS: Synergy: Collaborative Research: Distributed Just-Ahead-Of-Time Verification of Cyber-Physical Critical Infrastructure.” Adversaries who gain access to a cyber-physical system can cause significant physical damage and financial loss by injecting false data into a sensor node. Identifying adversarial action in a system can mitigate unsafe actions made based off of bad data. The technique presented in this work combines topology analysis with real-time probing to create a measure of trustworthiness of sensors in a system. A previously developed tool called Cyber Physical Security Assessment (CyPSA) gives each node a topology vulnerability score based on the cyber accessibility and potential physical impact should it be compromised. We develop a real-time vulnerability score by simulating attack and non-attack scenarios with PowerWorld. The data from these simulations is processed in MATLAB. Results show improved attack detection over current methods. The measure of trustworthiness developed will improve attack detection in power systems, and it may be used to help prevent a system from entering an unstable state

Trustee: A Trust Management System for Fog-enabled Cyber Physical Systems

In this paper, we propose a lightweight trust management system (TMS) for fog-enabled cyber physical systems (Fog-CPS). Trust computation is based on multi-factor and multi-dimensional parameters, and formulated as a statistical regression problem which is solved by employing random forest regression model. Additionally, as the Fog-CPS systems could be deployed in open and unprotected environments, the CPS devices and fog nodes are vulnerable to numerous attacks namely, collusion, self-promotion, badmouthing, ballot-stuffing, and opportunistic service. The compromised entities can impact the accuracy of trust computation model by increasing/decreasing the trust of other nodes. These challenges are addressed by designing a generic trust credibility model which can countermeasures the compromise of both CPS devices and fog nodes. The credibility of each newly computed trust value is evaluated and subsequently adjusted by correlating it with a standard deviation threshold. The standard deviation is quantified by computing the trust in two configurations of hostile environments and subsequently comparing it with the trust value in a legitimate/normal environment. Our results demonstrate that credibility model successfully countermeasures the malicious behaviour of all Fog-CPS entities i.e. CPS devices and fog nodes. The multi-factor trust assessment and credibility evaluation enable accurate and precise trust computation and guarantee a dependable Fog-CPS system

Cyber physical systems implementation for asset management improvement: A framework for the transition

Libro en Open AccessThe transformation of the industry due to recent technologies introduction is an evolving process whose engines are competitiveness and sustainability, understood in its broadest sense (environmental, economic and social). This process is facing, due to the current state of scientific and technological development, a new challenge yet even more important: the transition from discrete technological solutions that respond to isolated problems, to a global conception where the assets, plant, processes and engineering systems are conceived, designed and operated as an integrated complex unit. This vision is evolving besides a set of concepts that are, in some way, to guide this development: Smart Factories, Cyber-Physical Systems, Factory of the Future or Industry 4.0, are examples. The full integration of the operation and maintenance (O&M) processes in the production systems is a key topic within this new paradigm. Not only that, this evolution necessarily results in the emergence of new processes and needs of O&M, i.e. also, the O&M will undergo a profound transformation. The transition from actual isolated production assets to such Industry 4.0 with CPS is far from easy. This document presents a proposal to develop such transition adapting one iteration of the Model of Maintenance Management (MMM) integrated into ISO 55000 to the complexity of incorporating “System of Systems” CPSs maintenance. It involves several stages: identification, prioritization, risk management, planning, scheduling, execution, control, and improvement supported by system engineering techniques and agile/concurrent project managemen

A tool for monitoring and maintaining system trustworthiness at runtime

Trustworthiness of software systems is a key factor in their acceptance and effectiveness. This is especially the case for cyber-physical systems, where incorrect or even sub-optimal functioning of the system may have detrimental effects. In addition to designing systems with trustworthiness in mind, monitoring and maintaining trustworthiness at runtime is critical to identify issues that could negatively affect a system's trustworthiness. In this paper, we present a fully operational tool for system trustworthiness maintenance, covering a comprehensive set of quality attributes. It automatically detects, and in some cases mitigates, trustworthiness threatening events. The use of such a tool can enable complex software systems to support runtime adaptation and self-healing, thus reducing the overall upkeep cost and complexity