A framework for private and secure communication and interaction between agents interacting in transportation services is developed. An agent, i.e. a user, can ask questions or submit queries regarding whether the other agents, i.e. drivers, use the desired road at specific times of the day in an encrypted fashion. The authors developed the framework using semi-homomorphic encryption (namely, the Paillier's encryption method) to enable the algebraic manipulation of plain data without the need for decryption using appropriate computations over the encrypted data. Strong privacy and security guarantees are proved for the agents. Subsequently, the semi-homomorphic encryption method is utilised to develop privacy-aware ride-sharing and routing algorithms without the need for disclosing the origin and destination of the user.

Cyber attacks can cause cascading failures and blackouts in smart grids. Therefore, it is highly necessary to identify the types, impacts and solutions of cyber attacks to ensure the secure operation of power systems. As a well-known practice, steady-state analysis is commonly used to identify cyber attacks and provide effective solutions. However, it cannot fully cover non-linear behaviours and cascaded blackouts of the system caused by dynamic perturbations, as well as provide a post-disturbance operating point. This study presents a novel approach based on dynamic analysis that excludes the limitations of the steady-state analysis and can be used in the events of various cyber attacks. Four types of common attacks are reviewed, and their dynamic impacts are shown on the IEEE benchmark model of the Western System Coordinating Council system implemented in MATLAB Simulink. Then, recommendations are provided to enhance the security of the future smart power grids from the possible cyber attacks.

IoT cloud-based connected smart dustbins (equipped with sensors) are imperative for efficient waste management in smart city. Municipal agencies can reduce the use of both man and machine by cutting down their overall waste collection route distance as well as number of waste collection vehicles (WCVs) by deploying this proposed cyber-physical system for route optimization of WCVs with capacitated vehicle-routing model. A novel cost function is mathematically modelled using data from dustbin-sensors and real-time road-traffic with modified Dijkstra's algorithm for optimisation of WCVs routes. Amount of solid waste in the dustbin (GC in %), rate of the filling (ΔG) and real-time/dynamic road traffic information from Google distance matrix advanced application programming interface (API) are used for estimation of the optimised route for WCVs. Optimisation goal of this work is to reduce both capital expense (CapEx) and operational expense (OpEx) of solid waste collection in the city by cutting the WCV fleet size and reducing overall distance covered by WCVs. The proposed route optimisation technique is analytically simulated for Bhubaneswar smart city and the result shows 30.28% saving in overall WCVs route distance and hence reducing OpEx around 29.07% and CapEx around 26.83% by reducing WCV fleet size.

With the rapid development of data acquisition technology, many industries data already have the characteristics of big data and cloud technology has provided strong support for the storage and complex calculations of these massive data. The meteorological department established the cloud data centre based on the existing storage and computing resources and re-arranged the historical data to reduce the historical data access time of applications. However, the placement of each workflow and input data also affects the average data access time, which in turn affects the computing efficiency of the cloud data centre. At the same time, because of the collaborative processing of multiple nodes, the resource utilisation of cloud data centre has also been paid more and more attention. In addition, with the increase of data security requirements, some privacy conflict data should avoid being placed on the same or neighbouring nodes. In response to this challenge, based on the fat-tree network topology, this study proposes a data privacy protection-based collaborative placement strategy of workflow and data to jointly optimise the average data access time, the average resource utilisation, and the data conflict degree. Finally, a large number of experimental evaluations and comparative analyses verify the efficiency of the proposed method.

One of the basic requirements of today's sophisticated world is the availability of electrical energy, and neglect of this matter may have irreparable damages such as an extensive blackout. The problems which were introduced about the traditional power grid, and also, the growing advances in smart technologies make the traditional power grid go towards smart power grid. Although widespread utilisation of telecommunication networks in smart power grid enhances the efficiency of the system, it will create a critical platform for cyber attacks and penetration into the system. Automatic generation control (AGC) is a fundamental control system in the power grid, and it is responsible for controlling the frequency of the grid. An attack on the data transmitted through the telecommunications link from the sensors to the AGC will cause frequency deviation, resulting in disconnection of the load, generators and ultimately global blackout. In this study, by using a Kalman filter and a proposed detector, a solution has been presented to detect the attack before it can affect the system. Contrary to existing methods, this method is able to detect attacks that are stealthy from the area control error signal and χ²-detector. Simulations confirm the effectiveness of this method.

In this study, the authors consider the problem of exchanging secrete messages in cyber-physical systems (CPSs) without resorting to cryptographic solutions. In particular, they consider a CPS where the networked controller wants to send a secrete message to the plant. They show that such a problem can be solved by exploiting a Wyner wiretap-like encoding scheme taking advantage of the closed-loop operations typical of feedback control systems. Specifically, by resorting to the control concept of one-step reachable sets, they first show that a wiretap-like encoding scheme exists whenever there is an asymmetry in the plant model knowledge available to control system (the defender) and to the eavesdropper. The effectiveness of the proposed scheme is confirmed by means of a numerical example. Finally, they conclude the study by presenting open design challenges that can be addressed by the research community to improve, in different directions, the secrete message exchange problem in CPSs.

Low-frequency inter-area oscillation is one of the major problems to transfer the bulk power from one area to another area in an interconnected large power system. A wide-area signal-based controller is more effective to improve the damping of the inter-area oscillation than a local area signal-based controller. A wide-area measurement system makes it easier to transmit the wide-area signal through the communication system from the remote location to the controller site. However, the involvement of the unavoidable time delay in the wide-area signal transmission from a remote area to a controller site is to possess a great deal of challenge to design a damping controller. In this study, a unified Smith predictor (USP)-based loop shaping controller is designed to handle the negative effect of the delay using the wide-area signal. The robust stabilization normalised co-prime factor problem is converted into a generalised H _∞ optimisation problem for additional pole placement constraints. The performances of the USP-based loop-shaping H _∞ controller are compared with the USP-based H _∞ controller. From the obtained results, it is verified that the proposed controller gives an excellent damping performance and handles the effect of time delay.

Improving the availability and reliability of a fleet of mobile cyber–physical systems as well as the ability to adapt the maintenance planning decisions when facing unexpected events at the fleet level is a major stake faced by the manufacturers and the operators. In the context of this study, the authors propose a reactive multi-agent system model for the fleet maintenance planning of mobile cyber–physical systems. For that purpose, the ANEMONA multi-agent design methodology is used. In this methodology, the agents are modelled and then their organisational and interaction views are described. Numerical experiments are carried out in static and dynamic contexts. In a static context, the proposed multi-agent system is compared with a mathematical programming model to validate the effectiveness of the former in satisfying the fleet's availability and reliability expectations. In a dynamic context, simulated perturbations are used to illustrate the reactivity of the proposed multi-agent system. Lastly, an application to rail transport for the maintenance of a fleet of trains at Bombardier Transportation France is proposed. For that purpose, the proposed multi-agent system is integrated in the model layer of a decision support system named ‘MainFleet’ which is currently under development.

This study presents a formal description and verification method of the ontology transformation process of the distribution network information model based on the meta-model theory. By defining the dynamic change structures and model mapping constraints of the ontology transformation process of distribution network, a formalised specification for describing the key attributes of model updating and model mapping processes was constructed. The model updating and model mapping instances were specified using model checking verification tool SPIN. The method fundamentally guarantees the standardisation and reliability of the model ontology transformation process achieved by the meta-model.

In this study, an observer based control strategy is proposed for load frequency control (LFC) scheme against cyber-attack uncertainties. Most of research work focused on detection scheme or delay estimation scheme in presence of cyber-attack vulnerabilities and paid less attention on design of counteractive robust control scheme for LFC problem. Thus, observer based control scheme is designed here and provides robust performance against unknown input attack uncertainty and communication time-delay attack uncertainty. The generalized extended state observer (GESO) is used not only for state and disturbance estimation but also for disturbance rejection of the system. The said observer ensures accurate estimation of the actual states leading to convergence of estimation error to zero. So, the observer based linear quadratic regulator (LQR) is used to regulate the closed-loop damping ratio against cyber-attack uncertainty. In addition to fast response in terms of settling time and reduced over/undershoots, the proposed control scheme satisfactorily compensates the cyber-attack uncertainties in power system cyber physical networks and also compared with existing traditional PI and PID controllers. The simulation results demonstrate the robustness in terms of stability and effectiveness in terms of system security with proposed controller when subjected to cyber-attack uncertainties and load disturbances.