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Abstract Vehicle‐to‐everything communication systems play a crucial role in enhancing road safety and traffic efficiency through vehicle and roadside infrastructure interactions. To provide robust defences against external threats in secure and trustworthy information exchange, these systems utilise public key infrastructure to authenticate vehicle‐to‐everything participant identities with digital certificates and security credential management systems to administer these certificates and encryption keys. However, even with these defences, vulnerabilities persist, particularly from vehicles with legitimate certificates that may malfunction or be exploited for malicious purposes. To address these issues, this paper introduces a misbehaviour detection (MBD) system, notable for its combined use of local and global MBD algorithms. This system is specifically designed to combat both conventional and novel threats, including slander attacks, in which vehicles with legitimate certificates may be falsely accused, and sophisticated attacks targeting the global MBD system itself. The efficacy of our MBD system was rigorously validated at K‐City, the leading autonomous vehicle technology testing facility in Korea, demonstrating its ability to identify and counter internal misbehaviours precisely.

Abstract Quantum key distribution (QKD) provides a method of ensuring security using the laws of physics, avoiding the risks inherent in cryptosystems protected by computational complexity. Here, the authors investigate the feasibility of satellite‐based quantum key exchange using low‐cost compact nano‐satellites. The first prototype of system level quantum key distribution aimed at the Cube satellite scenario is demonstrated. It consists of a transmitter payload, a ground receiver and simulated free space channel to verify the timing and synchronisation (T&S) scheme designed for QKD and the required high loss tolerance of both QKD and T&S channels. The transmitter is designed to be deployed on various up‐coming nano‐satellite missions in the UK and internationally. The effects of channel loss, background noise, gate width and mean photon number on the secure key rate (SKR) and quantum bit error rate (QBER) are discussed. The authors also analyse the source of QBER and establish the relationship between effective signal noise ratio (ESNR) and noise level, signal strength, gating window and other parameters as a reference for SKR optimisation. The experiment shows that it can tolerate the 40 dB loss expected in space to ground QKD and with small adjustment decoy states can be achieved. The discussion offers valuable insight not only for the design and optimisation of miniature low‐cost satellite‐based QKD systems but also any other short or long range free space QKD on the ground or in the air.

Abstract The authors study the energy efficiency (EE) of ambient backscatter communication (AmBC) device‐assisted and reconfigurable intelligent surfaces (RIS)‐assisted non‐orthogonal multiple access (NOMA) downlinks. The authors establish two optimisation problems based on the two collaborative devices (AmBC devices, RIS) with the objective of maximising the EE of the system, taking into account the requirements of power limitation and rate limitation, etc. and also obtain the solutions of two problems by optimising the relevant performance metrics based on the alternating optimisation algorithm. For the backscatter device (BD)‐aided downlink NOMA network, the problem is first decoupled into three subproblems, where the power allocation optimisation subproblem is solved by using the quadratic transformation method and the subgradient algorithm. The maximum EE is obtained by iterating according to the Dinkelbach's algorithm. For the RIS‐aided downlink NOMA network, the power allocation problem is solved by the same method as above and the phase optimisation problem is solved by the successive convex approximation method. Numerical results show that the proposed algorithm can achieve convergence after several iterations, and the EE of systems with BD‐assisted and RIS‐assisted have different levels of sensitivity to different influencing factors.

Abstract The rapidly developing discipline of quantum computing (QC) employs ideas from quantum physics to improve the performance of traditional computers and other devices. Because of the dramatically improved speed at which it processes data, it can be applied to various issues. QC has many potential applications, but three of the most exciting applications are unstructured search, quantum simulation, and network optimisation. Several existing technologies, such as machine learning, may benefit from its increased speed and precision. In this study, the authors will explore how the principles of QC might be applied to the Internet of Things (IoT) to improve its accuracy, speed, and security. Several approaches exist for achieving this goal, such as network optimisation in IoT using QC, faster computation at IoT endpoints, securing IoT using QC, a quantum sensor for IoT, quantum digital marketing, quantum‐secured smart lock etc.

Abstract Communication security has become particularly crucial with the rapid development of the Internet of Things (IoT). Frequency hopping spread spectrum (FHSS) technology, a prevalent method in wireless communication, has a wide range of applications in the Internet of Things. Enhancing the security of frequency hopping sequences is an essential means to improve the security of frequency hopping communication in the Internet of Things, as the performance of frequency hopping sequences plays a crucial role in frequency hopping systems. This paper proposes constructing secure adaptive frequency hopping sequence sets based on the advanced encryption standard (AES) algorithm. As a block cipher algorithm with superior security, the AES algorithm can provide a fundamental guarantee for the security of the proposed frequency hopping sequences. The mapping methods from ciphertext sequences to frequency hopping sequences proposed in this paper can achieve the construction of frequency hopping sequences of any frequency set size to meet the requirements of adaptive frequency hopping. In addition, we also model and analyse the problem of overlapping spectrum band of the IoT groups in the industrial, scientific, and medical (ISM) band, aiming to achieve better packet transmission performance by adjusting the frequency set size.

Abstract Malicious domains provide malware with covert communication channels which poses a severe threat to cybersecurity. Despite the continuous progress in detecting malicious domains with various machine learning algorithms, maintaining up‐to‐date various samples with fine‐labeled data for training is difficult. To handle these issues and improve the detection accuracy, a novel malicious domain detection method named MDND‐SS‐PO is proposed that combines semi‐supervised learning and parameter optimization. The contributions of the study are as follows. First, the method extracts the statistical features of the IP address, TTL value, the NXDomain record, and the domain name query characteristics to discriminate Domain‐Flux and Fast‐Flux domain names simultaneously. Second, an improved DBSCAN based on the neighborhood division is designed to cluster labeled data and unlabeled data with low time consumption. Then, based on the clustering hypothesis, unlabeled data is tagged with pseudo‐label according to the cluster results, which aims to train a supervised classifier effectively. Finally, Gaussian process regression is used to optimize parameter settings of the algorithm. And the Silhouette index and F1 score are introduced to evaluate the optimization results. Experimental results show that the proposed method achieved a precise detection performance of 0.885 when the ratio of labeled data is 5%.

Abstract As a potential solution to improve wireless security, specific emitter identification is a lightweight access authentication technology. However, the existed deep learning‐based specific emitter identification methods are highly dependent on the training sample size, leading to serious overfitting problem when the training samples are inadequate, which obstructs their practical applications. To address this issue, an innovative data augmentation method to effectively expand the sample size is proposed. In this design, after data preprocessing, a random integration based data augmentation is applied to integrate several initial samples and generate new samples. Furthermore, compared with the existed methods, chaotic sequences are utilized to randomly set the integration weight of each initial sample, and thus enhancing the diversity of augmented samples. The superiority of the proposed chaotic integration‐based data augmentation method in accuracy, generalization ability and robustness is validated by the hardware implementation on digital mobile radio portable radios.

Abstract B5G/6G networks are facing challenges in the deployment of additional base stations. However, Taiwan's four major operators have launched VoWi‐Fi calling services to maintain signal quality and coverage for customers. These services pose potential threats when users connect to untrusted Wi‐Fi networks. Therefore, the authors utilised commercial equipment to study the security of VoWi‐Fi calling services offered by Taiwan's four major telecom companies. The authors employed address resolution protocol attack methods to develop two verification attacks that bypass existing security measures: one for dropping session initiation protocol packets and the other for dropping voice call packets, both capable of circumventing current security defences. Through real‐world experiments, the authors confirmed their feasibility and assessed their potential harm. Consequently, two defence methods are proposed. The first is an anti‐attack algorithm for app and device manufacturers to detect the security of the user's calling environment. The second is a recommendation for telecom operators to implement new detection mechanisms to safeguard user rights. The cover image is based on the Case Study VoWi‐Fi security threats: Address resolution protocol attack and countermeasures by Kuan‐Chu Lu et al., https://doi.org/10.1049/ntw2.12113

Abstract The evolution of Connected and Autonomous Vehicles (CAVs) promises improvements in our travel experience and the potential to enhance road safety and reduce environmental impact. This will be utilising highly diverse traffic environments that enable several advanced mobility applications. A secure, efficient, reliable, and resilient communications infrastructure is required to support developments in these CAV systems. Next generation of telecommunication networks will seamlessly integrate terrestrial, satellite, and airborne networks into a single wireless system satisfying the requirements of trustworthy future transport systems. Given the increasing importance of CAVs, coupled with their attractiveness as a cyber‐attack for threat agents (e.g., disruption of transportation systems by nation states), security is paramount. Future communications systems offer an opportunity to integrate Quantum Key Distribution (QKD) into vehicular environments, protecting against advances in quantum computation that render many of the classical algorithms that underpin Public Key Infrastructure obsolete. This paper proposes a method for the integration of QKD in V2I networks to enable secure data communication. Quantum Key Distribution is used in the end‐to‐end path of vehicle‐to‐infrastructure (V2I) networks. Furthermore, an overarching Software‐Defined Network, with integrated QKD, is introduced. We have investigated the security performance of QKD in a V2I network over an urban environment.

Abstract The security of data communications is one of the crucial challenges that our society is facing today. Quantum Key Distribution (QKD) is one of the most prominent methods for guaranteeing ultimate security based on the laws of quantum physics. In this work, the results obtained during the Italian Industry 4.0 Quantum Testbed (II4QuTe) project are reported where the authors realised a QKD testbed securely connecting the Competence Industry Manufacturing 4.0 (CIM4.0) located in Torino and a TIM edge node located 10 km away from the testbed. The edge node accommodates the server providing computation capabilities for managing the real‐time data generated by the machines within the CIM4.0 digital factory pilot line, thus gracefully integrating QKD with the MEC (Multi‐access Edge Computing) paradigm. The experiment was conducted for more than 69 h, establishing an average key generation rate of 5.125 keys/s (AES‐256 keys) and demonstrating the stability of the entire end‐to‐end encryption system.

Abstract In order to solve the security problems caused by malicious nodes in wireless sensor networks, a TS‐BRS reputation model based on time series analysis is proposed in this paper. By using the time series analysis method, the matching analysis of two time series is carried out to reduce the interference of channel conflicts on the reputation evaluation model and improve the accuracy of model recognition. In order to improve the adaptability of the evaluation model, the adaptive maintenance function μ is introduced into the update of credit value, which aggravates the influence of node behaviour on credit value at the present stage. The simulation results show that the new reputation evaluation model can effectively improve the detection rate and detection speed of malicious nodes in the network. After the introduction of maintenance function, the reputation value of the captured malicious nodes in the network has a faster convergence speed.

Abstract In recent years, key generation schemes based on the reciprocity of wireless channels have gained widespread attention in the field of wireless physical layer security. However, due to the openness of wireless channels, eavesdroppers may obtain partial legitimate keys by eavesdropping on the wireless channel. To address this issue, this paper proposes a wireless channel coding scheme that induces an “avalanche” of errors for eavesdroppers, which could maximize eavesdropper's bit error rate. The design of this scheme is based on the significant differences between the eavesdropping channel and the legitimate channel, and the average bit key disagreement ratio of the keys generated by the legitimate channel is around 8%. The scheme selects polar codes with strong error correction capabilities and chooses a coding rate matching the error level of the legitimate channel, forcing the eavesdropping channel's error rate into an “avalanche” state, where the error rate approaches 50%. This paper presents the structure of the encoder and determines the coding rate through simulation. Simulation results demonstrate that this scheme can significantly degrade the error rate of the eavesdropping channel while ensuring the prevention of eavesdroppers from obtaining secret information transmitted through the legitimate channel.

Abstract Quantum‐based technologies will provide system engineers with new capabilities for securing data communications. The UK AirQKD project has implemented a Free‐Space Optical Quantum Key Distribution (QKD) system to enable the continuous generation of symmetric encryption keys. One of the use cases for the generated keys is to secure Vehicle‐to‐Everything (V2X) communications. V2X applications would benefit from the certificate‐free security provided by QKD for a post‐quantum society. How FSO‐QKD could integrate into a V2X architecture is examined. An overview of V2X is provided with the role that FSO‐QKD could secure V2X data though some obstacles exist. One of the issues with 6G communications is the potential line‐of‐sight (LOS) considerations between the V2X devices. The modelling required for LOS is examined to analyse the outage performance of the building to infrastructure links in the 6G architecture. The results from the model show that further work is required if 6G LOS communications are going to be relied upon for future safety‐critical V2X applications.

Abstract Quasi‐chaotic generators are used for producing a pseudorandom behaviour that can be used for encryption/decryption and secure communications, introducing an implementation of them based on quantum technology. Namely, the authors propose a quasi‐chaotic generator based on quantum modular addition and quantum modular multiplication and they prove that quantum computing allows the parallel processing of data, paving the way for a fast and robust multi‐channel encryption/decryption scheme. The resulting structure is validated by means of several experiments, which assessed the performance with respect to the original VLSI solution and ascertained the desired noise‐like behaviour.

Abstract The authors devised a protocol that allows two parties, who may malfunction or intentionally convey incorrect information in communication through a quantum channel, to verify each other's measurements and agree on each other's results. This has particular relevance in a modified version of the quantum coin flipping game. The key innovation of the authors’ work includes the new design of a quantum coin that excludes any advantage of cheating, by which the long‐standing problem of the fair design of the game is, affirmatively, solved. Furthermore, the analysis is extended to N‐parties communicating with each other, where multiple solutions for the verification of each player's measurement is proposed. The results in the N‐party scenario could have particular relevance for the implementation of future quantum networks, where verification of quantum information is a necessity.

Abstract Reconfigurable intelligent surface (RIS) has great potential in securing wireless transmission, and it can flexibly change the wireless communication environment. However, the employment of RIS increases the difficulty in beamforming of base station (BS), and existing schemes cannot be directly utilized to enhance the security of system. Therefore, a reinforcement learning framework to jointly control BS and RIS for the purpose of enhancing the secure performance is proposed. Specifically, the beamforming ia transformed with artificial noise and reflection control as a Markov decision problem (MDP) in complex domain. Then, we develop the deep deterministic policy gradient based on complex‐valued neural networks (CV‐DDPG) to imitate the rules of complex computation. Additionally, the CV‐DDPG is performed as the agent of reinforcement learning to control the BS and RIS, which enables better utilization of the implied phase information of complex values in the system. The simulation results show that the proposed model promotes the performance of the control and greatly improves the secrecy rate of the legitimate user.

Abstract Here, the issue of physical layer security in a two‐way multi‐antenna relay network) is studied. In such a network, two multi‐antenna transceivers attempt to exchange their secret messages via a multi‐antenna relay node in the presence of an eavesdropper. Throughout the first hop, two sources send their messages to the relay node, while an eavesdropper tries to overhear these messages. Then, in the second hop, the relay attempts to send its signal in the null‐space direction of relay‐to‐eavesdropper channel to prevent eavesdropping. The main goal is to obtain effective receive and transmit beamforming vectors at transceivers as well as the beamforming matrix at the relay node to address the secrecy rate balancing problem. The underlying problem is not convex in general. To overcome this issue, the original problem is divided into three subproblems. In the first subproblem the beamforming design at the relay is optimized while in the second subproblem the receive beamforming in a closed form solution is obtained. Finally, in the last subproblem the transmit beamforming is solved using the semi‐definite relaxation and Taylor series expansion. Numerical results represent the effectiveness of the proposed method compared to the previous works in the literature.

Abstract The authors propose a secure intelligent reflecting surface (IRS) assisted transmission system in the presence of a ground eavesdropper, where the source in the ground transmits confidential information to unmanned aerial vehicle (UAV), IRS is deployed to promote the transmission rate of the source to UAV. Closed‐form expression for secure transmission non‐outage probability is derived, and secure transmission performance is analyzed. Simulation validates the correctness of the derivation. Compared with benchmarks, results show that the IRS can improve the secure transmission of ground to UAV.

Abstract As automobile intelligence continues to develop, the electronic control units connected to the Controller Area Network (CAN) bus within vehicles face an increasing number of threats from potential attacks originating from the internet. To address this issue, an intrusion detection and defence method is proposed that is capable of detecting illegal messages through the use of frequency anomaly detection, and subsequently disrupting them through utilization of the CAN bus arbitration mechanism. This proposed method offers a simple implementation compared to traditional approaches, while being able to identify suspicious units and neutralize threats in real‐time. Experimental results demonstrate the effectiveness of this approach.

Abstract In this paper, a joint detection strategy of Willie based on two phases observation is proposed and an energy‐efficient covert communication scheme with an adaptive assist nodes group (AANG) based on uniform jamming power (UJP) strategy is proposed to against the joint‐phase detection of Willie, which achieves covert communication with lower energy cost and higher average covert rate (ACR). The probability of detection error (PDE) at Willie with joint‐phase detection and ACR are derived. Furthermore, the optimal power allocation of legitimate transmitters is resolved to maximize ACR. Numerical results demonstrate the benefit of the proposed scheme over the covert rate and consumed jamming power.

Abstract Cyber‐physical systems (CPS) integrate control, sensing, and processing into interconnected physical components to support applications within transportation, energy, healthcare, environment, and various other areas. Secure and reliable wireless communication between devices is necessary to enable the widespread adoption of these emerging technologies. Cyber‐physical systems devices must be protected against active threats, such as Radio Frequency (RF) Jammers, which intentionally disrupt communication links. Jamming detection and mitigation techniques must be evaluated extensively to validate algorithms prior to full implementation. Challenges related to obtaining zoning permits, Federal Aviation Administration (FAA) pilot certification for Unmanned Aerial Vehicles (UAVs), and Federal Communications Commission (FCC) licencing lead to evaluation limited to simulation‐based or simplistic, non‐representative hardware experimentation. A site‐specific ray‐tracing emulation framework is presented to provide a realistic evaluation of communication devices under RF jamming attacks in complex scenarios involving mobility, vehicular, and UAV systems. System architecture and capabilities are provided for the devices under test, real‐world jamming adversaries, channel modelling, and channel emulation. Case studies are provided to demonstrate the use of the framework for different applications and jamming threats. The experimental results illustrate the benefit of the ray‐tracing emulation system for conducting complex wireless communication studies under the presence of RF jamming.

Abstract Traditional range query methods of work still have shortcomings in node energy consumption and privacy security, so a two‐layer secure and efficient range query method for wireless sensor networks is proposed. In the data storage stage, the sensing node obtains the data ciphertext and timestamp by the Advanced Encryption Standard encryption algorithm, receives the new encryption constraint chain by the reverse 0–1 encoding method and Hash‐based Message Authentication Code encryption algorithm, and sends the chain to the storage node. In the query response phase, the storage node responds to the request of the base station and sends the data that meet the query requirements. After receiving the data, the base station verifies the consistency with the new encryption constraint chain and timestamp. During the experiment, the energy consumption is analysed from three aspects: the number of data collected in the period, the data length of the sensing node and the partition factor of the encryption constraint chain. The results show that this method has low energy consumption and can maintain the consistency of data.

Abstract Global navigation satellite Systems (GNSS) are highly susceptible to various interferences because of their inherent vulnerability. In these interferences, induced spoofing is very difficult to be detected because it can gradually drag off the tracking points without unlocking the tracking loops of the attacked receiver and cause the victim to obtain a wrong position and/or time information. Furthermore, it is also very difficult to generate induced spoofing data, including simulation data and real data, to evaluate various induced spoofing detection and suppression algorithms. Existing generation algorithms need to precisely control and adjust many parameters of GNSS simulation software even for simulation data. To address this problem, this study proposes a GNSS‐induced spoofing simulation algorithm based on path planning. First, through given planned paths, the proposed algorithm independently generates the authentic and spoofing signals without changing the parameters of GNSS simulation software. After that, the induced spoofing simulation data are synthesised by only adjusting the powers of authentic and spoofing signals. The effectiveness of the proposed algorithm is verified by the positioning solutions and the correlation function outputs of the code and carrier tracking loops.

Abstract Quantum Information Splitting is an important technique used in Quantum Communication where a sender has to comply with more than one recipient for quantum teleportation. We have shown that three sets of three‐qubit GHZ states can be used to realize the splitting of an arbitrary three‐qubit state securely. We propose a scheme by a new quantum circuit and simulate them on the IBM quantum experience platform and conclude that an arbitrary three‐qubit state can be split up experimentally by using three GHZ states. In a way, the presented protocol is deterministic and secure against eavesdropping attacks.

Abstract Quantum key distribution (QKD) systems enable secure key generation between two parties. Such systems require an authenticated classical channel for QKD protocols to work. Usually, the initial authentication key for this channel is pre‐shared. In this work, methods that are used to renew the pre‐shared keys ensuring a high level of security and performance for the subsequent quantum key generation are discussed. The model of QKD systems in terms of the lifecycle of the keys is formalised and a full set of parameters that can be used for key renewal functions is described. A detailed adversary model allows us to compare key renewal schemes by the probabilities of successful attacks and their consequences. As a result, it is shown that a hybrid key renewal scheme, which uses both the auxiliary pre‐shared key and a part of the quantum sequence, has the higher security properties among considered schemes and is recommended to be used in QKD systems.

Abstract Wireless sensor networks (WSNs) are becoming more popular in recent times due to the availability of low cost, the short transmission range of sensor nodes and their easy deployment in different application areas; however, security is crucial for WSNs due to the nature of data they transmit in most cases in their locations. Sensor nodes transmit through an open medium and due to the short communication range of each sensor node, a node may need to transmit through many hops to a final destination. Denial‐of‐service (DoS) is one of the attacks that can be launched against WSNs to prevent legitimate nodes from transmitting/receiving data packets. Developing an attack detection and countermeasure system to mitigate the effect of DoS is not an easy task. This work proposes lightweight models for DoS attack detection in WSNs. We developed different lightweight models and algorithms for the detection and elimination of DoS in WSNs and experimented the same. The performance of data delivery ratio, delay, detection rate, energy consumption, and false‐positive was carried out. The experimental results show that the proposed scheme achieved a high true‐positive detection rate, low false‐positive detection rate, energy‐efficient, and high data reliability. Numerical examples are presented to further validate the effectiveness of the proposed scheme.

Increasing penetrations of interoperable distributed energy resources (DER) in the electric power system are expanding the power system attack surface. Maloperation or malicious control of DER equipment can now cause substantial disturbances to grid operations. Fortunately, many options exist to defend and limit adversary impact on these newly-created DER communication networks, which typically traverse the public internet. However, implementing these security features will increase communication latency, thereby adversely impacting real-time DER grid support service effectiveness. In this work, a collection of software tools called SCEPTRE was used to create a co-simulation environment where SunSpec-compliant photovoltaic inverters were deployed as virtual machines and interconnected to simulated communication network equipment. Network segmentation, encryption, and moving target defence security features were deployed on the control network to evaluate their influence on cybersecurity metrics and power system performance. The results indicated that adding these security features did not impact DER-based grid control systems but improved the cybersecurity posture of the network when implemented appropriately.

This study presents a hybrid data-driven physics model-based framework for real-time monitoring in smart grids. As the power grid transitions to the use of smart grid technology, it's real-time monitoring becomes more vulnerable to cyber-attacks like false data injections (FDIs). Although smart grids cyber-physical security has an extensive scope, this study focuses on FDI attacks, which are modelled as bad data. State-of-the-art strategies for FDI detection in real-time monitoring rely on physics model-based weighted least-squares state estimation solution and statistical tests. This strategy is inherently vulnerable by the linear approximation and the companion statistical modelling error, which means it can be exploited by a coordinated FDI attack. In order to enhance the robustness of FDI detection, this study presents a framework which explores the use of data-driven anomaly detection methods in conjunction with physics model-based bad data detection via data fusion. Multiple anomaly detection methods working at both the system level and distributed local detection level are fused. The fusion takes into consideration the confidence of the various anomaly detection methods to provide the best overall detection results. Validation considers tests on the IEEE 118-bus system.

Strong adaptive radar, such as cognitive radar (CNR), can perform various missions while ensuring its own security in electronic warfare, via detecting environments and changing the radar parameters in real time. Unfortunately, most of the current military countermeasures, such as jamming-based electronic countermeasures, have rarely been related to jamming for CNR. Since the behaviours of radar in the traditional design of the jammer-radar scenario are always static, it is easy to create a subjective or local optimal jamming effect. In order to dynamically analyse the execution process of a complete jamming radar mission, this work establishes an equivalent attack-defence game in which the radar is regarded as a defence decision agent, and the jammer is an attack decision agent. The attributes of the game's players, the rules of the game, and the conditions for the end of the game are set clearly by setting reasonable parameters. After searching for antagonism strategies by exhaustive method, it can be found that the survivability of the predictive cognitive jamming is much stronger than that of the normal jamming based on real-time sampling data of radars. This conclusion is demonstrated through a 1 ms simulation of the game process.

In well-managed coordinated networked microgrids (MGs) besides electricity interchange between MGs, global optimisation is fulfilled. Here the authors studied a networked MG architecture, in which the control centre of microgrids communicates with a distribution network operator (DNO) to fulfil their local requirements. However, communication signals are always vulnerable to cyberattacks. While the surplus/deficit powers are reported by one MG to DNO, other MGs can act as potential cyber attackers aimed at decreasing their own costs. This action may also lead to threat the global optimisation of networked MGs. When an attacker manipulates the signal sent from the attacked MG to DNO, it will result in a false power interchange schedule produced by DNO. The attacker MG in the next step, maliciously accesses and changes the signal sent from the DNO to the attacked MG. In case a successful attack executed, the operation cost of the attacker MG will be decreased. Furthermore, a game-theoretic model of attacker–defender interaction is proposed, while different behaviours of players are addressed. The optimal scheduling scheme of MGs is formulated as a mixed-integer linear programming problem and solved by CPLEX. Simulation results show the impacts of the attacks and importance of the defend strategies.

Internet of Things (IoT), cloud computing and wireless medical sensor networks have significantly improved remote healthcare monitoring. In a healthcare monitoring system, many resource-limited sensors are deployed to sense, process and communicate the information. However, continuous and accurate operations of these devices are very important, especially in the infant incubator monitoring system. Because important decisions are made on the received information. Therefore, it is necessary to ensure the authenticity between the incubator monitoring system and doctors. In this work, a public key encryption based computationally efficient mutual authentication protocol is proposed for secure data transmission between incubator monitoring systems and doctors or administrators. The proposed protocol improves performance and reduces the computational cost without compromising the security. The security analysis part shows the strength of the proposed protocol against various attacks, performance analysis part shows that the proposed protocol performs better than other existing protocol based on Rivest–Shamir–Adleman and elliptic-curve cryptography schemes.

The messages in vehicular ad hoc networks (VANET) are vulnerable to attack in the open wireless environment. Group communication in VANET is receiving more attention, which confronts many security issues. First, only users who have passed legal authentication can communicate in the group. The ring signature is an effective solution. In addition, the group membership in the vehicular self-organising network changes rapidly, which leads to dynamic adjustment of group members. It is necessary to consider the computing power and communication capability of each node in the group members. To speed up the authentication process, a roadside unit with more computing power and communication capability than vehicles is selected as the signature agent, which effectively reduces the computational load of vehicles and accelerates the communication throughput. Meanwhile, the computational task and communication overhead have not been well-solved. To address these issues, this paper proposed an efficient proxy ring signature scheme for VANET to achieve higher signature efficiency and lower transmission overhead. The scheme allows both privacy protection and original signer tracing. Security analysis shows that the proposed scheme meets the security requirements of VANET.

Wireless sensor networks consist of a collection of sensors to monitor physical or environmental events. Nowadays, the sensor networks are used in important applications like military, health and civilian monitoring. Since it is a wireless medium, deployed in remote locations and resource-constrained nature, the sensor networks are easily vulnerable to attacks. The attack creates significant damages to the sensor networks. To avoid these problems, intrusion detection system (IDS) is implemented at the base station to filter any abnormal packets. In the proposed system, a survey is made on the attacks and rules to detect the attacks. Filtering the attacks using rule-based IDS at the sensor nodes would reduce the amount of packet transmission to the base station which, in turn, would reduce the energy consumption of the sensor network. Extreme learning machine (ELM) algorithm is implemented at the base station to detect the abnormal packets. The experimental result shows the performance of different classification techniques and cross-layer rules over the NSL-KDD and real-time datasets. The detection rate of the ELM algorithm is higher compared to other systems.

In this study, the authors propose a scheme based on Stackelberg game for price and power control in threshold-based relay network, where the source transmits message to destination with the cooperation of a relay, in the presence of an eavesdropper. The relay gets revenue for transmitting the source information and the source profits from the cooperation secrecy rate. The source needs to pay for the amount of power allocated by the relay for transmission of source data to destination. Threshold-based relaying is considered, where the relay can correctly decode the message, only if the received signal satisfies the predetermined threshold. Maximal ratio combining scheme is employed at destination and eavesdropper to maximise the probability of secure transmission and successful eavesdropping, respectively. Unlike other works to date, the authors have maximised the utility of relay and source, with allocated maximum power constraints at the relay node, using Stackelberg security game scheme. The closed-form optimal solution for price and power control is obtained, for this leader–follower security equilibrium game model, with the help of convex optimisation.

Extensive deployment of interoperable distributed energy resources (DER) is increasing the power system cyber security attack surface. National and jurisdictional interconnection standards require DER to include a range of autonomous and commanded grid-support functions, which can drastically influence power quality, voltage, and bulk system frequency. Here, the authors investigate the impact to the cyber-physical power system in scenarios where communications and operations of DER are controlled by an adversary. The findings show that each grid-support function exposes the power system to distinct types and magnitudes of risk. The physical impact from cyber actions was analysed in cases of DER providing distribution system voltage regulation and transmission system support. Finally, recommendations are presented for minimising the risk using engineered parameter limits and segmenting the control network to minimise common-mode vulnerabilities.

In recent years, cyber-physical system (CPS) applications have been extensively utilised in the electric power grid to enable wide-area protection, control, and monitoring of power systems. Many of these applications in a smart grid CPS depend on reliable time synchronisation. For example, synchrophasor data from geographically distributed phasor measurement units (PMU) utilise global positioning system (GPS) for precise timing. However, these units are exposed to GPS time spoofing attacks that can lead to inaccurate monitoring and trigger unnecessary, and possibly destabilising, remedial control actions. The authors develop an end-to-end case study demonstrating the effect of GPS spoofing attacks on the phase angle monitoring and control functions of a PMU-based load shedding scheme. The evaluation of authors attack strategy is performed in a hardware-in-the-loop real-time digital simulator-enabled power system testbed.

In this study, the authors propose a state space modelling approach for trust evaluation in wireless sensor networks. In their state space trust model (SSTM), each sensor node is associated with a trust metric, which measures to what extent the data transmitted from this node would better be trusted by the server node. Given the SSTM, they translate the trust evaluation problem to be a non-linear state filtering problem. To estimate the state based on the SSTM, a component-wise iterative state inference procedure is proposed to work in tandem with the particle filter (PF), and thus the resulting algorithm is termed as iterative PF (IPF). The computational complexity of the IPF algorithm is theoretically linearly related with the dimension of the state. This property is desirable especially for high-dimensional trust evaluation and state filtering problems. The performance of the proposed algorithm is evaluated by both simulations and real data analysis.

Cyber-physical systems (CPS) help create new services and applications by revolutionising our world in different fields through their tight interactions and automated decisions. This is especially true with the ongoing increase in the number of physical things (sensors, actuators, smartphones, tablets, and so on) along with the explosive increase in the usage of online networking services and applications. Future fifth generation (5G) cellular networks will facilitate the enabling of CPS communications over current network infrastructure through different technologies such as device-to-device (D2D) communications. In this study, the authors discuss about the main challenges that cellular providers will face as the massive number of CPS devices attempt to access the cellular spectrum. A case study is presented on how to ease the spectrum access of these devices through D2D spatial spectrum sensing. Furthermore, the authors discuss about protecting these D2D links from eavesdropping, since security is becoming a critical aspect in the cyber-physical space, especially with the large amount of traffic that is constantly flowing through the network.

This paper presents an assessment of how successful an eavesdropping attack on a contactless payment transaction can be in terms of bit and frame error rates, using an easily concealable antenna and low-cost electronics. Potential success of an eavesdropping attack largely depends on the correct recovery of the data frames used in the ISO 14443 standard. A near-field communication inductive loop antenna was used to emulate an ISO 14443 transmission. For eavesdropping, an identical inductive loop antenna as well as a shopping trolley modified to act like an antenna were used. The authors present and analyse frame error rates obtained with the authors equipment over a range of distances, up to 100 cm, well above the official maximum operating distance depending on the magnetic field strength.

Internet of Things (IoT), cloud computing and wireless medical sensor networks have significantly improved remote healthcare monitoring. In a healthcare monitoring system, many resource-limited sensors are deployed to sense, process and communicate the information. However, continuous and accurate operations of these devices are very important, especially in the infant incubator monitoring system. Because important decisions are made on the received information. Therefore, it is necessary to ensure the authenticity between the incubator monitoring system and doctors. In this work, a public key encryption based computationally efficient mutual authentication protocol is proposed for secure data transmission between incubator monitoring systems and doctors or administrators. The proposed protocol improves performance and reduces the computational cost without compromising the security. The security analysis part shows the strength of the proposed protocol against various attacks, performance analysis part shows that the proposed protocol performs better than other existing protocol based on Rivest-Shamir-Adleman and elliptic-curve cryptography schemes.