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It is widely held that debugging cyber-physical systems (CPS) is challenging; many strongly held beliefs exist regarding how CPS are currently debugged and tested and the suitability of various techniques. For instance, dissenting opinions exist as to whether formal methods (including static analysis, theorem proving, and model checking) are appropriate in CPS verification and validation. Simulation tools and simulation-based testing are also often considered insufficient for CPS. Many "experts" posit that high-level programming languages (e.g., Java or C#) are not applicable to CPS due to their inability to address (significant) resource constraints at a high level of abstraction. To date, empirical studies investigating these questions have not been done. In this paper, we qualitatively and quantitatively analyze why debugging CPS remains challenging and either dispel or confirm these strongly held beliefs along the way. Specifically, we report on a structured online survey of 25 CPS researchers (10 participants classified themselves as CPS developers), semistructured interviews with nine practitioners across four continents, and a qualitative literature review. We report these results and discuss several implications for research and practice related to CPS.

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Both academia and industry have directed tremendous interest toward the combination of Cyber Physical Systems and Cloud Computing, which enables a new breed of applications and services. However, due to the relative long distance between remote cloud and end nodes, Cloud Computing cannot provide effective and direct management for end nodes, which leads to security vulnerabilities. In this article, we first propose a novel trust evaluation mechanism using crowdsourcing and Intelligent Mobile Edge Computing. The mobile edge users with relatively strong computation and storage ability are exploited to provide direct management for end nodes. Through close access to end nodes, mobile edge users can obtain various information of the end nodes and determine whether the node is trustworthy. Then, two incentive mechanisms, i.e., Trustworthy Incentive and Quality-Aware Trustworthy Incentive Mechanisms, are proposed for motivating mobile edge users to conduct trust evaluation. The first one aims to motivate edge users to upload their real information about their capability and costs. The purpose of the second one is to motivate edge users to make trustworthy effort to conduct tasks and report results. Detailed theoretical analysis demonstrates the validity of Quality-Aware Trustworthy Incentive Mechanism from data trustfulness, effort trustfulness, and quality trustfulness, respectively. Extensive experiments are carried out to validate the proposed trust evaluation and incentive mechanisms. The results corroborate that the proposed mechanisms can efficiently stimulate mobile edge users to perform evaluation task and improve the accuracy of trust evaluation.

SummaryFog computing is used as a popular extension of cloud computing for a variety of emerging applications. To incorporate various design choices and customized policies in fog computing paradigm, Microservices is proposed as a new software architecture, which is easy to modify and quick to deploy fog applications because of its significant features, ie, fine granularity and loose coupling. Unfortunately, the Microservices architecture is vulnerable due to its wildly distributed interfaces that are easily attacked. However, the industry has not been fully aware of its security issues. In this paper, a survey of different security risks that pose a threat to the Microservices‐based fog applications is presented. Because a fog application based on Microservices architecture consists of numerous services and communication among services is frequent, we focus on the security issues that arise in services communication of Microservices in four aspects: containers, data, permission, and network. Containers are often used as the deployment and operational environment for Microservices. Data is communicated among services and is vital for every enterprise. Permission is the guarantee of services security. Network security is the foundation for secure communication. Finally, we propose an ideal solution for security issues in services communication of Microservices‐based fog applications.

It is well known that blink, yawn, and heart rate changes give clue about a human's mental state, such as drowsiness and fatigue. In this paper, image sequences, as the raw data, are captured from smart phones which serve as non-contact optical sensors. Video streams containing subject's facial region are analyzed to identify the physiological sources that are mixed in each image. We then propose a method to extract blood volume pulse and eye blink and yawn signals as multiple independent sources simultaneously by multi-channel second-order blind identification (SOBI) without any other sophisticated processing, such as eye and mouth localizations. An overall decision is made by analyzing the separated source signals in parallel to determine the driver's driving state. The robustness of the proposed method is tested under various illumination contexts and a variety of head motion modes. Experiments on 15 subjects show that the multi-channel SOBI presents a promising framework to accurately detect drowsiness by merging multi-physiological information in a less complex way. INDEX TERMS Yawn, blink, blood volume pulse (BVP), drowsiness detection, second-order blind identification (SOBI).