Titlebook: ICT Systems Security and Privacy Protection; 39th IFIP Internatio Nikolaos Pitropakis,Sokratis Katsikas,Konstantinos Conference proceedings

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Can Synthetic Data Preserve Manifold Properties?, high-dimensional feature spaces. This data may contain confidential information that must be safeguarded against disclosure. One way to make the data accessible could be by using anonymization. An alternative is to use synthetic data that mimics the behavior of the original data. GANs represent a p

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,Putting Authorization Servers on User-Owned Devices in User-Managed Access,the user’s consent for privacy. Although OAuth 2.0 is widely used for such authorization, it is a troublesome task for the users to manage authorization. User-Managed Access (UMA) is a framework for asynchronous user-centric authorization management. UMA aims to reduce the burden of users for handli

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,Chain of Trust: Unraveling References Among Common Criteria Certified Products,entangled with various kind of relations between the certified products. Yet, the prevalence and nature of dependencies among Common Criteria certified products remains largely unexplored. This study devises a novel method for building the graph of references among the Common Criteria certified prod

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,LightArmor: A Lightweight Trusted Operating System Isolation Approach for Mobile Systems,S), as a critical component of TEE, has exposed many vulnerabilities in recent years. With the high privilege of TOS, an attacker who gains control of TOS can take over arbitrary system components, and the privacy of the system can no longer be guaranteed. Although existing methods provide multiple

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,Satellite: Effective and Efficient Stack Memory Protection Scheme for Unsafe Programming Languages, attacks remain a significant threat. To mitigate the threat, various defense approaches have been proposed such as the Address Space Layout Randomization (ASLR) and Stack Canary. However, adversaries have demonstrated the capability to bypass them, which results in upgraded defense systems. To comp

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,Neurosymbolic Learning in the XAI Framework for Enhanced Cyberattack Detection with Expert Knowledgt defence mechanisms. The integration of expert knowledge can drastically enhance the efficacy of IoT network attack detection systems by enabling them to leverage domain-specific insights. This paper introduces a novel approach by applying Neurosymbolic Learning within the Explainable Artificial In

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