Access Special Section: Security Analytics and Intelligence for Cyber Physical Systems

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A Cyber Physical System (CPS) is a smart network system with actuators, embedded sensors, and processors to interact with the physical world by guaranteeing the performance and supporting real-time operations of safety critical applications. These systems drive innovation and are a source of competitive advantage in today's challenging world. By observing the behavior of physical processes and activating actions, CPS can alter its behavior to make the physical environment perform better and more accurately. By definition, CPS basically has two major components including cyber systems and physical processes. Examples of CPS include autonomous transportation systems, robotics systems, medical monitoring, automatic pilot avionics, and smart grids. Advances in CPS will empower scalability, capability, usability, and adaptability, which will go beyond the simple systems of today. At the same time, CPS has also increased cybersecurity risks and attack surfaces. Cyber attackers can harm such systems from multiple sources while hiding their identities. As a result of sophisticated threat matrices, insufficient knowledge about threat patterns, and industrial network automation, CPS has become extremely insecure. Since such infrastructure is networked, attacks can be prompted easily without much human participation from remote locations, thereby making CPS more vulnerable to sophisticated cyberattacks. In turn, large-scale data centers managing a huge volume of CPS data become vulnerable to cyber-attacks. To secure CPS, the role of security analytics and intelligence is significant. It brings together huge amounts of data to create threat patterns, which can be used to prevent cyber-attacks in a timely fashion. The primary objective of this Special Section in IEEE ACCESS is to collect a complementary and diverse set of articles, which demonstrate up-to-date information and innovative developments in the domain of security analytics and intelligence for CPS.
Our Call for Papers received a total of 58 high-quality submissions contributed by industry and academia, which were evaluated based on their quality, precision, and relevance to the theme of the Special Section. Out of them, 22 articles have been accepted for publication after a rigorous review process. The contents of these submissions are summarized below.
In the article by Li et al., ''A ciphertext-policy attributebased encryption based on an ordered binary decision diagram,'' the authors presented a Ciphertext-Policy Attribute-Based Encryption (CP-ABE) system based on the Ordered Binary Decision Diagram (OBDD) for ensuring the security of CPS and the Internet of Things (IoTs). The proposed scheme utilizes both the high calculating efficiency and powerful description ability of OBDD in order to improve the performance.
The article titled ''Context-aware verifiable cloud computing,'' by Yan et al., proposes a context-aware verifiable computing scheme based on fully homomorphic encryption in order to verify the accurateness of the processed results of encrypted data stored in the cloud. To serve this process, four different auditing protocols were designed by the researchers, which satisfy the security requirements. Furthermore, the performance of these protocols was evaluated through system simulation, algorithm implementation, and performance analysis.
In the work by Ali et al., ''An automatic digital audio authentication/forensics system,'' the authors propose a novel automatic authentication system with the ability to distinguish between original and forged audio. The proposed system categorizes audio from different environments recorded with the same microphone based on the psychoacoustic principles of hearing. For authentication, the Gaussian mixture model has been applied in order to make automatic decisions.
Lu et al., in the work titled ''Depth map reconstruction for underwater Kinect camera using inpainting and local image mode filtering,'' investigate the problem of underwater optical imaging used for security monitoring in oceans. To overcome shortcomings of the underwater image processing techniques, this research article proposes a Kinectbased underwater depth map estimation method. The proposed approach demonstrated high-accuracy results.
In the article ''A novel Internet of Things-centric framework to mine malicious frequent patterns,'' Usman et al. developed a framework for mining malicious frequent patterns for detecting misuse and distinguishing anomalies in an IoT deployment. This framework is then assessed by using three important ARM techniques including Apriori, FP-Growth, and Prefixspan from a Pakistan-based organization.
The article by Wang et al., ''Verification of implementations of cryptographic hash functions,'' is concerned with VOLUME 8, 2020 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see https://creativecommons.org/licenses/by/4.0/ the verification of cryptographic hash functions through the precision of protocol consistency. This article proposes an automated verification framework, VeriHash, which presents an innovative cryptographic model design in order to model semantics of hash function implementations, compositional verification for scalability, and protracted array theories for operations analysis. The proposed verification framework has been evaluated on two SHA-3 implementations. In the article by Wang et al., ''A fast feature fusion algorithm in image classification for cyber physical systems,'' the authors studied challenges associated with the establishment of Cyber Physical Systems (CPS) with image classification systems. The main contribution of this research is the fast feature fusion algorithm based on genetic algorithm, dynamic weight assignment, and partial selection method for CPS image classification. The experimental results demonstrate that the proposed approach can attain high classification accuracy with lower hardware consumption and training time.
In the article by Chen et al., ''Fast trajectory planning and robust trajectory tracking for pedestrian avoidance,'' the authors address the problem of pedestrian avoidance, due to which a high percentage of pedestrian accidents occur all over the world. The research proposed a method to quickly identify a feasible path for pedestrian avoidance while guaranteeing its feasibility.
In the article by Liu et al., ''SEDEA: State estimationbased dynamic encryption and authentication in smart grid,'' the authors address security issues present in the communication between Remote Terminal Units (RTUs) and Control Center (CC) in the smart grid through SEDEA. This scheme uses commands from CC and measurements reported from RTUs to generate encryption keys. Moreover, such an approach updates its key regularly in order to ensure secure communication.
In the article by Khan et al., ''A continuous change detection mechanism to identify anomalies in ECG signals for WBAN-based healthcare environments,'' the researchers have paid attention to an important concern regarding forgery of ECG data being transmitted from sensors to Personal Server (PS). This research makes use of a simplified Markov model-based detection mechanism to determine that intrusion has been occurred.
The article ''Evidential network modeling for cyberphysical system state inference,'' by Friedberg et al., discusses monitoring of CPS to detect deviances from normal operations in order to support timely and accurate control decisions. This research presented evidential networks for state inference in CPS, which assists in identifying causality between higher and lower level system states.
The work by Xu et al., ''Achieving efficient detection against false data injection attacks in smart grid,'' discusses an efficient real-time decision scheme to prevent False Data Injection Attack (FDIA) in state estimation. It is widely used in system monitoring of smart grids. The simulation results demonstrated that the scheme is efficient.
The work titled ''Privacy preservation in e-Healthcare environments: State of the art and future directions,'' by Sahi et al., presents the challenges in preserving the privacy of patient records in e-Healthcare. Furthermore, this research also reviews several privacy preservation mechanisms being deployed in e-Healthcare.
In the article ''A novel data analytical approach for false data injection cyber-physical attack mitigation in smart grids,'' Wang et al. developed a data analytical approach based on a data-centric paradigm in order to detect False Data Injection Attacks (FDIAs). This research makes use of the Margin Setting Algorithm (MSA) to detect time attack and playback attack. The proposed scheme is then compared with two other popular schemes including Artificial Neural Network (ANN) and Support Vector Machine (SVM). The results demonstrate that the proposed approach works efficiently.
In the article by Mehmood et al., ''Secure knowledge and cluster-based intrusion detection mechanism for smart wireless sensor networks,'' the authors present a knowledge-based context-aware scheme to deal with security issues present in wireless sensor networks (WSNs). This scheme manages intrusions produced by malicious nodes with the help of the knowledge base placed at the base station. Cluster Heads (CHs), in turn, gather categorized events from the knowledge base and block maliciously repeated activities.
Loukas et al., in the work titled, ''Cloud-based cyberphysical intrusion detection for vehicles using deep learning,'' investigate the recognition of cyber-attacks against vehicles. Since vehicles can manage limited processing resources, lightweight techniques can be employed. This research covers such a limitation through computational offloading based on deep learning. This research has further developed a mathematical model to determine possessing and latency of the approach, which turns out to be efficient in case of a reliable network.
The research article by Li et al., titled ''Gender identification via reposting behaviors in social media,'' studies gender identification over social networks through reposting behaviors. This research proposed an approach supported by homophily and four intuitive procedures by integrating knowledge of statistics and sociology. The experimental results demonstrate the accuracy of the proposed scheme.
In the work by Napiah et al., ''Compression header analyzer intrusion detection system (CHA-IDS) for 6LoWPAN communication protocol,'' the authors present CHA-IDS, which addresses the detection of combined routing attacks by capturing and handling raw data for data collection, system actions, and data analysis. It makes use of correlation-based feature selection to determine required features, which are then tested by means of six machine learning algorithms. Experimental results demonstrate that the proposed scheme is efficient.
The article ''A critical analysis of mobility management related issues of wireless sensor networks in cyber physical systems,'' authored by Al-Muhtadi et al., studied mobility management problems in CPS and WSN. The major con-208196 VOLUME 8, 2020 tribution of this research is to evaluate existing mobility management approaches against quadruple set of metrics.
In the article by Cheon et al., ''Toward a secure drone system: Flying with real-time homomorphic authenticated encryption,'' the authors investigate security issues of networked vehicle systems. This research proposed a linearly homomorphic authenticated encryption (LinHAE) approach to secure vehicle systems against forgery and eavesdropping attacks.
The work titled ''Security analysis of smartphone and cloud computing authentication frameworks and protocols,'' by Siddiqui et al., addresses an important concern of today's world regarding the security and authenticity of information. The authors performed a review and security analysis of cloud computing and smartphone authentication protocols and frameworks to analyze authentication challenges.
The invited article ''A survey on mobile edge networks: Convergence of computing, caching and communications,'' by Wang et al., reviews mobile edge networks and issues associated with caching, communication technologies, and computing at the network edge. Furthermore, it presents use cases and applications of mobile edge networks and concludes with a review of several future directions.
Finally, the leading editor and the guest editors of the Special Section express their gratitude to the authors for their contributions to the volunteering referees for their dedication and to the whole IEEE ACCESS editorial staff for their invaluable support.

HAIDER ABBAS, Lead Guest Editor National University of Sciences and Technology (NUST)
Islamabad 44000, Pakistan