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This editorial gives an overview of the papers included in the Special Issue on “Security, Privacy, and Trustworthiness of Sensor Networks and Internet of Things” of Sensors. The context of the special issue theme is first briefly described. This is then followed by an outline of each paper that provides information on the problem addressed; the proposed solution/approach; and, where relevant, the results of the evaluation of the proposed solution.

In various domains such as energy, manufacturing, and maritime, cyber–physical systems (CPSs) have seen increased interest. Both academia and industry have focused on the cybersecurity aspects of such systems. The assessment of cyber risks in a CPS is a popular research area with many existing approaches that aim to suggest relevant methods and practices. However, few works have addressed the extensive and objective evaluation of the proposed approaches. In this paper, a standard-aligned evaluation methodology is presented and empirically conducted to evaluate a newly proposed cyber risk assessment approach for CPSs. The approach, which is called FMECA-ATT&CK is based on failure mode, effects and criticality analysis (FMECA) risk assessment process and enriched with the semantics and encoded knowledge in the Adversarial Tactics, Techniques, and Common Knowledge framework (ATT&CK). Several experts were involved in conducting two risk assessment processes, FMECA-ATT&CK and Bow-Tie, against two use cases in different application domains, particularly an autonomous passenger ship (APS) as a maritime-use case and a digital substation as an energy-use case. This allows for the evaluation of the approach based on a group of characteristics, namely, applicability, feasibility, accuracy, comprehensiveness, adaptability, scalability, and usability. The results highlight the positive utility of FMECA-ATT&CK in model-based, design-level, and component-level cyber risk assessment of CPSs with several identified directions for improvements. Moreover, the standard-aligned evaluation method and the evaluation characteristics have been demonstrated as enablers for the thorough evaluation of cyber risk assessment methods.

As maritime operations become increasingly reliant on interconnected information technology (IT) and operational technology (OT) systems, ensuring cybersecurity on vessels has become more critical than ever. One of these systems is the Integrated Navigation System (INS), which assists the Officer of Watch (OOW) on the bridge in ensuring safe navigation. The INS comprises several components that may be susceptible to cyber attacks, hence it faces cyber risks that need to be mitigated. Cyber risks are understood differently, depending on perspective. In this paper, we determine the perspective that the research community has of cyber risk, focusing on the INS, and that of professionals representing the maritime industry, and analyze similarities and differences. To this end, we conduct a systematic literature review and interviews with maritime professionals. This study provides useful insights for researchers and professionals seeking to understand the cyber risks of the INS.

Several disruptive attacks against companies in the maritime industry have led experts to consider the increased risk imposed by cyber threats as a major obstacle to undergoing digitization. The industry is heading toward increased automation and connectivity, leading to reduced human involvement in the different navigational functions and increased reliance on sensor data and software for more autonomous modes of operations. To meet the objectives of increased automation under the threat of cyber attacks, the different software modules that are expected to be involved in different navigational functions need to be prepared to detect such attacks utilizing suitable detection techniques. Therefore, we propose a systematic approach for analyzing the navigational NMEA messages carrying the data of the different sensors, their possible anomalies, malicious causes of such anomalies as well as the appropriate detection algorithms. The proposed approach is evaluated through two use cases, traditional Integrated Navigation System (INS) and Autonomous Passenger Ship (APS). The results reflect the utility of specification and frequency-based detection in detecting the identified anomalies with high confidence. Furthermore, the analysis is found to facilitate the communication of threats through indicating the possible impact of the identified anomalies against the navigational operations. Moreover, we have developed a testing environment that facilitates conducting the analysis. The environment includes a developed tool, NMEA-Manipulator that enables the invocation of the identified anomalies through a group of cyber attacks on sensor data. Our work paves the way for future work in the analysis of NMEA anomalies toward the development of an NMEA intrusion detection system.

Safeguarding both safety and cybersecurity is paramount to the smooth and trustworthy operation of contemporary cyber physical systems, many of which support critical functions and services. As safety and security have been known to be interdependent, they need to be jointly considered in such systems. As a result, various approaches have been proposed to address safety and cybersecurity co-engineering in cyber physical systems. This paper provides a comprehensive survey of safety and cybersecurity co-engineering methods, and discusses relevant open issues and research challenges. Despite the extent of the existing literature, several aspects of the subject still remain to be fully addressed.

The e-navigation concept was introduced by the IMO to enhance berth-to-berth navigation towards enhancing environmental protection, and safety and security at sea by leveraging technological advancements. Even though a number of e-navigation testbeds including some recognized by the IALA exist, they pertain to parts only of the Integrated Navigation System (INS) concept. Moreover, existing e-navigation and bridge testbeds do not have a cybersecurity testing functionality, therefore they cannot be used for assessing the cybersecurity posture of the INS. With cybersecurity concerns on the rise in the maritime domain, it is important to provide such capability. In this paper we review existing bridge testbeds, IMO regulations, and international standards, to first define a reference architecture for the INS and then to develop design specifications for an INS Cyber-Physical Range, i.e., an INS testbed with cybersecurity testing functionality.

The enforcement of fine-grained access control policies in constrained dynamic networks can become a challenging task. The inherit constraints present in those networks, which result from the limitations of the edge devices in terms of power, computational capacity and storage, require an effective and efficient access control mechanism to be in place to provide suitable monitoring and control of actions and regulate the access over the resources. In this article, we present RESPOnSE, a framework for the specification and enforcement of security policies within such environments, where the computational burden is transferred to high-tier nodes, while low-tier nodes apply risk-aware policy enforcement. RESPOnSE builds on a combination of two widely used access control models, Attribute-Based Access Control and Role-Based Access Control, exploiting the benefits each one provides. Moreover, the proposed mechanism is founded on a compensatory multicriteria decision-making algorithm, based on the calculation of the Euclidean distance between the run-time values of the attributes present in the security policy and their ideal values, as those are specified within the established policy rules.

In recent times, security and safety are, at least, conducted in safety-sensitive or critical sectors. Nevertheless, both processes do not commonly analyze the impact of security risks on safety. Several scholars are focused on integrating safety and security risk assessments, using different methodologies and tools in critical infrastructures (CIs). Bayesian networks (BN) and graph theory (GT) have received much attention from academia and industries to incorporate security and safety features for different CI applications. Hence, this study aims to conduct a systematic literature review (SLR) for co-engineering safety and security using BN or GT. In this SLR, the preferred reporting items for systematic reviews and meta-analyses recommendations (PRISMA) are followed. Initially, 2295 records (acquired between 2011 and 2020) were identified for screening purposes. Later on, 240 articles were processed to check eligibility criteria. Overall, this study includes 64 papers, after examining the pre-defined criteria and guidelines. Further, the included studies were compared, regarding the number of required nodes for system development, applied data sources, research outcomes, threat actors, performance verification mechanisms, implementation scenarios, applicability and functionality, application sectors, advantages, and disadvantages for combining safety, and security measures, based on GT and BN. The findings of this SLR suggest that BN and GT are used widely for risk and failure management in several domains. The highly focused sectors include studies of the maritime industry (14%), vehicle transportation (13%), railway (13%), nuclear (6%), chemical industry (6%), gas and pipelines (5%), smart grid (5%), network security (5%), air transportation (3%), public sector (3%), and cyber-physical systems (3%). It is also observed that 80% of the included studies use BN models to incorporate safety and security concerns, whereas 15% and 5% for GT approaches and joint GT and BN methodologies, respectively. Additionally, 31% of identified studies verified that the developed approaches used real-time implementation, whereas simulation or preliminary analysis were presented for the remaining methods. Finally, the main research limitations, concluding remarks and future research directions, are presented

Social media are getting more and more ingrained into everybody’s lives. With people’s more substantial presence on social media, threat actors exploit the platforms and the information that people share there to deploy and execute various types of attacks. This paper focuses on the Norwegian population, exploring how people perceive risks arising from the use of social media, focusing on the analysis of specific indicators such as age, sexes and differences among the users of distinct social media platforms. For data collection, a questionnaire was structured and deployed towards the users of multiple social media platforms (total n = 329). The analysis compares risk perceptions of using the social media platforms Facebook (n = 288), Twitter (n = 134), Reddit (n = 189) and Snapchat (n = 267). Furthermore, the paper analyses the differences between the sexes and between the digital natives and non-natives. Our sample also includes sufferers of ID theft (n = 50). We analyse how account compromise occurs and how suffering ID theft changes behaviour and perception. The results show significant discrepancies in the risk perception among the social media platform users across the examined indicators, but also explicit variations on how this affects the associated usage patterns. Based on the results, we propose a generic risk ranking of social media platforms, activities, sharing and a threat model for SoMe users. The results show the lack of a unified perception of risk on social media, indicating the need for targeted security awareness enhancement mechanisms focusing on this topic.

There is a growing interest in using social robots in public spaces for indoor and outdoor applications. The threat landscape is an important research area being investigated and debated by various stakeholders. Objectives: This study aims to identify and synthesize empirical research on the complete threat landscape of social robots in public spaces. Specifically, this paper identifies the potential threat actors, their motives for attacks, vulnerabilities, attack vectors, potential impacts of attacks, possible attack scenarios, and mitigations to these threats. Methods: This systematic literature review follows the guidelines by Kitchenham and Charters. The search was conducted in five digital databases, and 1469 studies were retrieved. This study analyzed 21 studies that satisfied the selection criteria. Results: Main findings reveal four threat categories: cybersecurity, social, physical, and public space. Conclusion: This study completely grasped the complexity of the transdisciplinary problem of social robot security and privacy while accommodating the diversity of stakeholders’ perspectives. Findings give researchers and other stakeholders a comprehensive view by highlighting current developments and new research directions in this field. This study also proposed a taxonomy for threat actors and the threat landscape of social robots in public spaces.