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The Consumer-Oriented Trusted Service Manager (CO-TSM) model has been recognised as a significant advancement in managing applications on Near Field Communication (NFC)-enabled mobile devices and multi-application smart cards. Traditional Trusted Service Manager (TSM) models, while useful, often result in market fragmentation and limit widespread adoption due to their centralised control mechanisms. The CO-TSM model addresses these issues by decentralising management and offering greater flexibility and scalability, making it more adaptable to the evolving needs of embedded systems, particularly in the context of the Internet of Things (IoT) and Radio Frequency Identification (RFID) technologies. This paper provides a comprehensive analysis of the CO-TSM model, highlighting its application in various technological domains such as smart cards, HCE-based NFC mobile phones, TEE-enabled smart home IoT devices, and RFID-based smart supply chains. By evaluating the CO-TSM model’s architecture, implementation challenges, and practical deployment scenarios, this paper demonstrates how CO-TSM can overcome the limitations of traditional TSM approaches. The case studies presented offer practical insights into the model’s adaptability and effectiveness in real-world scenarios. Through this examination, the paper aims to underscore the CO-TSM model’s role in enhancing scalability, flexibility, and user autonomy in secure embedded device management, while also identifying areas for future research and development.

Near-Field Communication (NFC) has enabled mobile devices to emulate contactless smart cards, which has also rendered them susceptible to relay attacks. Numerous countermeasures have been proposed that use ambient sensors as an anti-relay mechanism. However, there are concerns regarding their efficacy in time-critical scenarios, such as transport ticketing and contactless payments. This paper empirically and comprehensively evaluates whether ambient sensors are an effective anti-relay mechanism for such NFC-based contactless transactions. To this end, we examine 17 sensors available via the Android platform. Each sensor, where feasible, was used to record measurements in 1,000 contactless transactions with 252 users across four physical locations. We then conduct an extensive four-part evaluation using similarity metrics, traditional machine learning models, and deep learning methods used in existing work and beyond. We conclude that mobile ambient sensors are currently unsuitable for detecting relay attacks on NFC contactless transactions under realistic timing constraints, contrary to the suggestions and proposals made in existing work.

Current Peer-to-Peer (P2P) energy market models raise serious concerns regarding the confidentiality and integrity of energy consumption, trading and billing data. While Distributed Ledger Technology (DLT) systems (e.g., blockchain) have been proposed to enhance security, an attacker could damage other parts of the model, such as its infrastructure: an adversarial attacker could target the communication between entities by, e.g., eavesdropping or modifying data. The main goal of this paper is to propose a model for a decentralised P2P marketplace for trading energy, which addresses the problem of developing security and privacy-aware environments. Additionally, a Multi-Agent System (MAS) architecture is presented with a focus on security and sustainability. In order to propose a solution to DLT’s scalability issues (i.e., through transaction confirmation delays), off-chain state channels are considered for the energy negotiation and resolution processes. Additionally, a STRIDE (spoofing, tampering, repudiation, information disclosure, denial of service, elevation of privilege) security analysis is conducted within the context of the proposed model to identify potential vulnerabilities.