Digital world has produced efficiencies, new innovative products, and close customer relationships globally by the effective use of mobile, IoT (Internet of Things), social media, analytics and cloud technology to generate models for better decisions. Blockchain is recently introduced and revolutionizing the digital world bringing a new perspective to security, resiliency and efficiency of systems. While initially popularized by Bitcoin, Blockchain is much more than a foundation for crypto currency. It offers a secure way to exchange any kind of good, service, or transaction. Industrial growth increasingly depends on trusted partnerships; but increasing regulation, cybercrime and fraud are inhibiting expansion. To address these challenges, Blockchain will enable more agile value chains, faster product innovations, closer customer relationships, and quicker integration with the IoT and cloud technology. Further Blockchain provides a lower cost of trade with a trusted contract monitored without intervention from third parties who may not add direct value. It facilitates smart contracts, engagements, and agreements with inherent, robust cyber security features. This paper is an effort to break the ground for presenting and demonstrating the use of Blockchain technology in multiple industrial applications. A healthcare industry application, Healthchain, is formalized and developed on the foundation of Blockchain using IBM Blockchain initiative. The concepts are transferable to a wide range of industries as finance, government and manufacturing where security, scalability and efficiency must meet.

This paper analyzes the notion of resilience in power systems from a fundamental viewpoint and thoroughly examines its practical implications. The paper aims to describe and classify different high-impact rare (HR) events, provide a more technical definition of power system resilience, and discuss linkages between resilience and other well-stablished concepts such as security, and reliability. Most relevant decisions of system operators in the face of HR events involve a significant level of stress and strain. In order to make informed decisions within this context, it is crucial to have an all-inclusive picture of the state of the system. This paper provides an appropriate framework that not only characterizes the various states of the system, but also derives informed decisions from a resilience-oriented perspective. It also describes and analyzes diverse resilience improvement strategies. Comprehensive models and classifications are provided to clearly capture various aspects of power system resilience.

Smart power grids are being enhanced by adding communication infrastructure to improve their reliability, sustainability, and efficiency. Despite all of these significant advantages, their open communication architecture and connectivity renders the power systems' vulnerability to a range of cyber-attacks. This paper proposes a novel resilient control system for Load Frequency Control (LFC) system under false data injection (FDI) attacks. It is common to use encryption in data transfer links as the first layer of defending mechanism; here, we proposed a second defense layer that can jointly detect and mitigate FDI attacks on power systems. Here, we propose a new anomaly detection (AD) technique which consists of a Luenberger observer and an artificial neural network (ANN). Since FDI attacks can happen rapidly, the observer structure is enhanced by the Extended Kalman filter (EKF) to improve the ANN ability for online detection and estimation. The resilient controller is designed based on the attack estimation, which can eliminate the need for control reconfiguration. The resiliency of the proposed design against FDI attacks is tested on the LFC system. The simulation results clearly show that the proposed control system can successfully detect anomalies and compensate for their adverse effects.

Faults and failures in the system components are two main reasons for the instability and the degradation in control performance. In recent decades, fault-tolerant control (FTC) approaches have been introduced to improve the resiliency of control systems against faults and failures. In general, FTC techniques are classified into active and passive approaches. This paper reviews fault and failure causes in control systems and discusses the latest solutions that are introduced to make the control system resilient.The recent achievements in fault detection and isolation (FDI) approaches and active FTC designs are investigated. Furthermore, a thorough comparison of several different aspects is conducted to understand the advantage and disadvantages of various FTC techniques to motivate researchers to further developing FTC and FDI approaches.

In networked control systems (NCS), agents participating in a network share their data with others to work together. When agents share their data, they can naturally expose the NCS to layers of faults and cyber-attacks, which can contribute to the propagation of error from one agent/area to another within the system. One common type of attack in which adversaries corrupt information within a NCS is called a false data injection (FDI) attack. This paper proposes a control scheme which enables a NCS to detect and mitigate FDI attacks and at the same time compensate for measurement noise and process noise. Furthermore, the developed controller is designed to be robust to unknown inputs. The algorithm incorporates a Kalman filter as an observer to estimate agents' states. We also develop a neural network (NN) architecture to detect and respond to any anomalies caused by FDI attacks. The weights of the NN are updated using an extended Kalman filter, which significantly improves the accuracy of FDI detection. A simulation of the results is provided which illustrates satisfactory performance of the developed method to accurately detect and respond to FDI attacks.