Biblio

This work-in-progress paper proposes a design methodology that addresses the complexity and heterogeneity of cyber-physical systems (CPS) while simultaneously proving resilient control logic and security properties. The design methodology involves a formal methods-based approach by translating the complex control logic and security properties of a water flow CPS into timed automata. Timed automata are a formal model that describes system behaviors and properties using mathematics-based logic languages with precision. Due to the semantics that are used in developing the formal models, verification techniques, such as theorem proving and model checking, are used to mathematically prove the specifications and security properties of the CPS. This work-in-progress paper aims to highlight the need for formalizing plant models by creating a timed automata of the physical portions of the water flow CPS. Extending the time automata with control logic, network security, and privacy control processes is investigated. The final model will be formally verified to prove the design specifications of the water flow CPS to ensure efficacy and security.

Deep Learning has been proven more effective than conventional machine-learning algorithms in solving classification problem with high dimensionality and complex features, especially when trained with big data. In this paper, a deep learning binomial classifier for Network Intrusion Detection System is proposed and experimentally evaluated using the UNSW-NB15 dataset. Three different experiments were executed in order to determine the optimal activation function, then to select the most important features and finally to test the proposed model on unseen data. The evaluation results demonstrate that the proposed classifier outperforms other models in the literature with 98.99% accuracy and 0.56% false alarm rate on unseen data.

Critical Infrastructure represents the basic facilities, services and installations necessary for functioning of a community, such as water, power lines, transportation, or communication systems. Any act or practice that causes a real-time Critical Infrastructure System to impair its normal function and performance will have debilitating impact on security and economy, with direct implication on the society. SCADA (Supervisory Control and Data Acquisition) system is a control system which is widely used in Critical Infrastructure System to monitor and control industrial processes autonomously. As SCADA architecture relies on computers, networks, applications and programmable controllers, it is more vulnerable to security threats/attacks. Traditional SCADA communication protocols such as IEC 60870, DNP3, IEC 61850, or Modbus did not provide any security services. Newer standards such as IEC 62351 and AGA-12 offer security features to handle the attacks on SCADA system. However there are performance issues with the cryptographic solutions of these specifications when applied to SCADA systems. This research is aimed at improving the performance of SCADA security standards by employing NTRU, a faster and light-weight NTRU public key algorithm for providing end-to-end security.