Vehicular Social Networks (VSNs) have emerged as a new social interaction paradigm, where vehicles can form social networks on the roads to improve the convenience/safety of passengers. VSNs are part of Vehicle to Everything (V2X) services, which is one of the industrial verticals in the coming sixth generation (6G) networks. The lower latency, higher connection density, and near-100% coverage envisaged in 6G will enable more efficient implementation of VSNs applications. The purpose of this study is to address the problem of lateral movements of attackers who could compromise one device in a VSN, given the large number of connected devices and services in VSNs and attack other devices and vehicles. This challenge is addressed via our proposed Blockchain-based Collaborative Distributed Intrusion Detection (BCDID) system with a novel Dynamic Throttling Strategy (DTS) to detect and prevent attackers’ lateral movements in VSNs. Our experiments showed how the proposed DTS improve the effectiveness of the BCDID system in terms of detection capabilities and handling queries three times faster than the default strategy with 350k queries tested. We concluded that our DTS strategy can increase transaction processing capacity in the BCDID system and improve its performance while maintaining the integrity of data on-chain.

Privacy and data protection by design are relevant parts of the General Data Protection Regulation (GDPR), in which businesses and organisations are encouraged to implement measures at an early stage of the system design phase to fulfil data protection requirements. This paper addresses the policy and system architecture design and propose two variants of privacy policy language and architecture description language, respectively, for specifying and verifying data protection and privacy requirements. In addition, we develop a fully automated algorithm based on logic, for verifying three types of conformance relations (privacy, data protection, and functional conformance) between a policy and an architecture specified in our languages’ variants. Compared to related works, this approach supports a more systematic and fine-grained analysis of the privacy, data protection, and functional properties of a system. Our theoretical methods are then implemented as a software tool called DataProVe and its feasibility is demonstrated based on the centralised and decentralised approaches of COVID-19 contact tracing applications.

To address the challenges of internal security policy compliance and dynamic threat response in organizations, we present a novel framework that integrates artificial intelligence (AI), blockchain, and smart contracts. We propose a system that automates the enforcement of security policies, reducing manual effort and potential human error. Utilizing AI, we can analyse cyber threat intelligence rapidly, identify non-compliances and automatically adjust cyber defence mechanisms. Blockchain technology provides an immutable ledger for transparent logging of compliance actions, while smart contracts ensure uniform application of security measures. The framework's effectiveness is demonstrated through simulations, showing improvements in compliance enforcement rates and response times compared to traditional methods. Ultimately, our approach provides for a scalable solution for managing complex security policies, reducing costs and enhancing the efficiency while achieving compliance. Finally, we discuss practical implications and propose future research directions to further refine the system and address implementation challenges.

With the purpose of defending against lateral movement in today's borderless networks, Zero Trust Architecture (ZTA) adoption is gaining momentum. With a full scale ZTA implementation, it is unlikely that adversaries will be able to spread through the network starting from a compromised endpoint. However, the already authenticated and authorised session of a compromised endpoint can be leveraged to perform limited, though malicious, activities ultimately rendering the endpoints the Achilles heel of ZTA. To effectively detect such attacks, distributed collaborative intrusion detection systems with an attack scenario-based approach have been developed. Nonetheless, Advanced Persistent Threats (APTs) have demonstrated their ability to bypass this approach with a high success ratio. As a result, adversaries can pass undetected or potentially alter the detection logging mechanisms to achieve a stealthy presence. Recently, blockchain technology has demonstrated solid use cases in the cyber security domain. In this paper, motivated by the convergence of ZTA and blockchain-based intrusion detection and prevention, we examine how ZTA can be augmented onto endpoints. Namely, we perform a state-of-the-art review of ZTA models, real-world architectures with a focus on endpoints, and blockchain-based intrusion detection systems. We discuss the potential of blockchain's immutability fortifying the detection process and identify open challenges as well as potential solutions and future directions.

This paper addresses the problem of children's online safety in the context of the growing digital landscape. With a surge in the use of digital technology among children, there has been an increase in online safety harms, risks and criminal incidents despite existing data protection and online privacy protection regulations. Most general security and privacy assessment approaches/standards focus mainly on protecting businesses from financial loss, but there remains a notable gap in methodologies specifically designed to cater to the unique challenges faced by children in the online space. To fill this gap, we propose a safety risk assessment approach that focuses specifically on children's online safety. The key novelty of our approach is providing an explainable and systematic evaluation of potential safety weaknesses of online services and applications based on precise automated mathematical reasoning. This framework has the potential to assist online service and app designers during the system design phase enabling them to proactively ensure Safety-by-Design, as well as auditors and users to understand the risks posed by existing services/apps, promoting further research on designing age-appropriate warnings and education materials for children and parents.