Smart cyber-physical systems (CPSs) include Internet of things (IoT), smart grids, smart cities, smart transportation, and smart “Anything” (e.g., homes and hospitals). These systems require different levels of security and protection based the sensitivity of their data. Nonetheless, we are living in a world where cyber attacks, privacy violations, phishing scams, and data breaches have become commonplace. Smart CPSs are also subject to security violations and privacy breaches, which stem from the vulnerabilities of existing computers and communications technologies. In addition, as smart CPSs get more complex, more vulnerabilities will emerge. Hackers will be able to launch increasingly sophisticated attacks in the future due to the ever-shifting cyber physical landscape. Hence, innovative research is needed for security assurance and privacy preservation in smart CPSs for new architectural models, system designs, and cryptographical protocols.
In this special issue, we received 29 submissions from both academia and industry in the relevant fields. Following a strict review process, we accepted 12 papers for this special issue. Each of the papers was peer-reviewed by at least three experts in the field. In the following, we provide a brief introduction to each paper.
There are four papers aiming to design and analyze security schemes and privacy preserving strategies for IoT applications. The paper titled “Function-Aware Anomaly Detection Based on Wavelet Neural Network for Industrial Control Communication” proposed a function-aware anomaly detection approach to detect these cyber intrusions and anomalies. Next, the authors of the paper titled “A Compatible OpenFlow Platform for Enabling Security Enhancement in SDN” proposed a unified, lightweight platform, called the open security-enhanced compatible openFlow platform, to enhance the security property and facilitate the security configuration and evaluation. And in the paper of “User Presence Inference via Encrypted Traffic of Wireless Camera in Smart Homes”, the authors proposed a system (HomeSpy) that infers user presence by inspecting the intrinsic pattern of the wireless camera traffic. This system revealed that attackers are able to infer whether users are at home or not by eavesdropping the traffic of wireless cameras. Finally, in the paper titled “An Effective Integrity Verification Scheme of Cloud Data Based on BLS Signature”, the authors improved the previous privacy preserving model and proposed an effective integrity verification scheme of cloud data based on Boneh-Lynn-Shacham signature. This scheme can ensure public audition and data privacy preserving.
Intelligent transportation systems, also known as vehicular ad hoc networks (VANETs), are an extended application for cyber-physical systems. Privacy preserving is also one of key issues of VANETs. Automotive intelligence is built on the dynamic data collection and application of vehicles. Vehicle driving data, collected without owners’ knowledge, may be regarded as a big data gold mine so as to sale to third parties. This special issue included three papers in this topic. The paper titled “Towards a Novel Trust-Based Multicast Routing for VANETs” designed a novel trust-based multicast routing protocol to defend against multiple attacks and improve the routing efficiency. And in the work “Research on Trajectory Data Releasing Method via Differential Privacy Based on Spatial Partition”, the authors discussed disclosure of trajectory data and exploited differential privacy to publish and release trajectory data so as to ensure privacy and availability. In addition, because vehicles in VANETs can be treated as edge nodes, the authors of the paper titled “A Novel Differential Game Model-Based Intrusion Response Strategy in Fog Computing” studied the optimal intrusion response strategy and formulated a mathematical model based on differential game theory.
There are five papers focusing on privacy preserving in mobile social networks (MSNs). In the paper titled “Differentially Private Recommendation System Based on Community Detection in Social Network Applications”, the authors proposed a novel recommendation method that provided a list of recommendations for target attributes based on community detection and known user attributes and links. Secondly, the work in the paper titled “RPAR: Location Privacy Preserving via Repartitioning Anonymous Region in Mobile Social Network” investigated the problem of location privacy preserving in MSNs and minimized the traffic between the anonymous server and the LBS server while protecting the privacy of the user location. Thirdly, the authors of the paper titled “Privacy Preservation for Friend-Recommendation Applications” analyzed the privacy leakage of friend-recommendation applications in social networks and put forward a privacy protection mechanism based on zero knowledge without any privacy leakage to the application server. Fourthly, different from adding noises into the original data for privacy protection, the work “GANs Based Density Distribution Privacy-Preservation on Mobility Data” studied the problem of privacy-preservation of density distribution on mobility data for location-based services in MSNs. Lastly, in the paper titled “Achieving the Optimal -Anonymity for Content Privacy in Interactive Cyberphysical Systems”, the authors suggested using k-anonymity solutions based on two content privacy metrics to formulate the problem of achieving the optimal content privacy in interactive cyber-physical systems.
We would like to thank all the authors for their great contributions to the Special Issue of Security and Privacy for Smart Cyber-Physical Systems and thank all anonymous reviewers for their valuable comments which help the authors to further improve their papers. It is an honor for all of us to serve as Guest Editors at Security and Communication Networks.
Conflicts of Interest
The editors declare that they have no conflicts of interest regarding the publication of this Special Issue.
Liran Ma
Yan Huo
Chunqiang Hu
Wei Li