14,669 research outputs found

    Multi-Layer Cyber-Physical Security and Resilience for Smart Grid

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    The smart grid is a large-scale complex system that integrates communication technologies with the physical layer operation of the energy systems. Security and resilience mechanisms by design are important to provide guarantee operations for the system. This chapter provides a layered perspective of the smart grid security and discusses game and decision theory as a tool to model the interactions among system components and the interaction between attackers and the system. We discuss game-theoretic applications and challenges in the design of cross-layer robust and resilient controller, secure network routing protocol at the data communication and networking layers, and the challenges of the information security at the management layer of the grid. The chapter will discuss the future directions of using game-theoretic tools in addressing multi-layer security issues in the smart grid.Comment: 16 page

    SCADA System Testbed for Cybersecurity Research Using Machine Learning Approach

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    This paper presents the development of a Supervisory Control and Data Acquisition (SCADA) system testbed used for cybersecurity research. The testbed consists of a water storage tank's control system, which is a stage in the process of water treatment and distribution. Sophisticated cyber-attacks were conducted against the testbed. During the attacks, the network traffic was captured, and features were extracted from the traffic to build a dataset for training and testing different machine learning algorithms. Five traditional machine learning algorithms were trained to detect the attacks: Random Forest, Decision Tree, Logistic Regression, Naive Bayes and KNN. Then, the trained machine learning models were built and deployed in the network, where new tests were made using online network traffic. The performance obtained during the training and testing of the machine learning models was compared to the performance obtained during the online deployment of these models in the network. The results show the efficiency of the machine learning models in detecting the attacks in real time. The testbed provides a good understanding of the effects and consequences of attacks on real SCADA environmentsComment: E-Preprin

    A framework for Operational Security Metrics Development for industrial control environment

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    Security metrics are very crucial towards providing insights when measuring security states and susceptibilities in industrial operational environments. Obtaining practical security metrics depend on effective security metrics development approaches. To be effective, a security metrics development framework should be scope-definitive, objective-oriented, reliable, simple, adaptable, and repeatable (SORSAR). A framework for Operational Security Metrics Development (OSMD) for industry control environments is presented, which combines concepts and characteristics from existing approaches. It also adds the new characteristic of adaptability. The OSMD framework is broken down into three phases of: target definition, objective definition, and metrics synthesis. A case study scenario is used to demonstrate an instance of how to implement and apply the proposed framework to demonstrate its usability and workability. Expert elicitation has also be used to consolidate the validity of the proposed framework. Both validation approaches have helped to show that the proposed framework can help create effective and efficient ICS-centric security metrics taxonomy that can be used to evaluate capabilities or vulnerabilities. The understanding from this can help enhance security assurance within industrial operational environments

    A framework for Operational Security Metrics Development for industrial control environment

    Get PDF
    Security metrics are very crucial towards providing insights when measuring security states and susceptibilities in industrial operational environments. Obtaining practical security metrics depend on effective security metrics development approaches. To be effective, a security metrics development framework should be scope-definitive, objective-oriented, reliable, simple, adaptable, and repeatable (SORSAR). A framework for Operational Security Metrics Development (OSMD) for industry control environments is presented, which combines concepts and characteristics from existing approaches. It also adds the new characteristic of adaptability. The OSMD framework is broken down into three phases of: target definition, objective definition, and metrics synthesis. A case study scenario is used to demonstrate an instance of how to implement and apply the proposed framework to demonstrate its usability and workability. Expert elicitation has also be used to consolidate the validity of the proposed framework. Both validation approaches have helped to show that the proposed framework can help create effective and efficient ICS-centric security metrics taxonomy that can be used to evaluate capabilities or vulnerabilities. The understanding from this can help enhance security assurance within industrial operational environments
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