Abstract-In the emerging Industrial IoT era, Machine-toMachine (M2M) communication technology is considered as a key underlying technology for building Industrial IoT environments where devices (e.g., sensors, actuators, gateways) are enabled to exchange information with each other in an autonomous way without human intervention. However, most of the existing M2M protocols that can be also used in the Industrial IoT domain provide security mechanisms based on asymmetric cryptography resulting in high computational cost. As a consequence, the resource-constrained IoT devices are not able to support them appropriately and thus, many security issues arise for the Industrial IoT environment. Therefore, lightweight security mechanisms are required for M2M communications in Industrial IoT in order to reach its full potential. As a step towards this direction, in this paper, we propose a lightweight authentication mechanism, based only on hash and XOR operations, for M2M communications in Industrial IoT environment. The proposed mechanism is characterized by low computational cost, communication and storage overhead, while achieving mutual authentication, session key agreement, device's identity confidentiality, and resistance against the following attacks: replay attack, man-in-the-middle attack, impersonation attack, and modification attack.

Increasingly complex systems lead to an interweaving of security, safety, availability and reliability concerns. Most dependability analysis techniques do not include security aspects. In order to include security, a holistic risk model for systems is needed. In our novel approach, the basic failure cause, failure mode and failure effect model known from FMEA is used as a template for a vulnerability cause-effect chain, and an FMEA analysis technique extended with security is presented. This represents a unified model for safety and security cause-effect analysis. As an example the technique is then applied to a distributed industrial measurement system.

The increasing integration of computational components and physical systems creates cyber-physical system, which provide new capabilities and possibilities for humans to control and interact with physical machines. However, the correlation of events in cyberspace and physical world also poses new safety and security challenges. This calls for holistic approaches to safety and security analysis for the identification of safety failures and security threats and a better understanding of their interplay. This paper presents the application of two promising methods, i.e. Failure Mode, Vulnerabilities and Effects Analysis (FMVEA) and Combined Harm Assessment of Safety and Security for Information Systems (CHASSIS), to a case study of safety and security co-analysis of cyber-physical systems in the automotive domain. We present the comparison, discuss their applicabilities, and identify future research needs.

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Safety-critical Cyber-physical Systems (CPS) in vehicles are becoming more and more complex and interconnected. There is a pressing need for holistic approaches for safety and security analysis to address the challenges. System-Theoretic Process Analysis (STPA) is a top-down safety hazard analysis method, based on systems theory especially aimed at such systems. In contrast to established approaches, hazards are treated as a control problem rather than a reliability problem. STPA-Sec extends this approach to also include security analysis. However, when we applied STPA-Sec to real world use cases for joint safety and security analysis, a Battery Management System for a hybrid vehicle, we observed several limitations of the security extension. We propose improvements to address these limitations for a combined safety and security analysis. Our improvements lead to a better identification of high level security scenarios. We evaluate the feasibility of the improved co-analysis method in a self-optimizing battery management system. We also discuss the general applicability of STPA-Sec to high level safety and security analysis and the relation to automotive cybersecurity standards.