Related papers: Resilient Risk based Adaptive Authentication and A…
Nuclear monitoring must considered as high precedence against national security. Now with the increasing nuclear threats it is crucial to ensure that malicious entity never procure nuclear warheads. Which comprises the prevention of illegal…
With rapid advances in computing systems, there is an increasing demand for more effective and efficient access control (AC) approaches. Recently, Attribute Based Access Control (ABAC) approaches have been shown to be promising in…
Artificial intelligence (AI) and reinforcement learning (RL) have shown significant promise in wireless systems, enabling dynamic spectrum allocation, traffic management, and large-scale Internet of Things (IoT) coordination. However, their…
Performance of the existing physical layer authentication schemes could be severely affected by the imperfect estimates and variations of the communication link attributes used. The commonly adopted static hypothesis testing for physical…
We propose a design-time framework (named HYDRA-C) for integrating security tasks into partitioned real-time systems (RTS) running on multicore platforms. Our goal is to opportunistically execute security monitoring mechanisms in a…
We develop a queueing-theoretic framework to model the temporal evolution of cyber-attack surfaces, where the number of active vulnerabilities is represented as the backlog of a queue. Vulnerabilities arrive as they are discovered or…
AI systems have found a wide range of real-world applications in recent years. The adoption of edge artificial intelligence, embedding AI directly into edge devices, is rapidly growing. Despite the implementation of guardrails and safety…
In this paper, we study the problem of constructing projective systematic authentication schemes based on binary linear codes. In systematic authentication, a tag for authentication is generated and then appended to the information, also…
A major challenge to deploying cyber-physical systems with learning-enabled controllers is to ensure their safety, especially in the face of changing environments that necessitate runtime knowledge acquisition. Model-checking and automated…
Reinforcement Learning (RL) is a powerful method for controlling dynamic systems, but its learning mechanism can lead to unpredictable actions that undermine the safety of critical systems. Here, we propose RL with Adaptive Regularization…
Remote identity verification is essential for modern digital security; however, it remains highly vulnerable to sophisticated Presentation Attacks (PAs) that utilise forged or manipulated identity documents. Although Deep Learning (DL) has…
Modern cloud and enterprise systems rely on identity-centric authorization, assuming that callers possessing valid credentials are safe to execute commands. The emergence of autonomous AI agents invalidates this assumption: agents can…
Content moderation for large language models (LLMs) remains a significant challenge, requiring flexible and adaptable solutions that can quickly respond to emerging threats. This paper introduces Retrieval Augmented Rejection (RAR), a novel…
Advanced persistent threats (APTs) pose significant challenges for organizations, leading to data breaches, financial losses, and reputational damage. Existing provenance-based approaches for APT detection often struggle with high false…
Modern operating systems increasingly randomize Media Access Control (MAC) addresses to protect user privacy, fundamentally disrupting Network Access Control (NAC) systems that have relied on MAC addresses as persistent device identifiers…
The evolution of networked systems, driven by innovations in software-defined networking (SDN), network function virtualization (NFV), open radio access networks (O-RAN), and cloud-native architectures, is redefining both the operational…
Cybersecurity threat and risk analysis (RA) approaches are used to identify and mitigate security risks early-on in the software development life-cycle. Existing approaches automate only parts of the analysis procedure, leaving key…
This report - a major revision of its previous release - describes a reference architecture for intelligent software agents performing active, largely autonomous cyber-defense actions on military networks of computing and communicating…
Large language models (LLMs) achieve impressive performance across diverse tasks yet remain vulnerable to jailbreak attacks that bypass safety mechanisms. We present RAID (Refusal-Aware and Integrated Decoding), a framework that…
Responsible disclosure limitation is an iterative exercise in risk assessment and mitigation. From time to time, as disclosure risks grow and evolve and as data users' needs change, agencies must consider redesigning the disclosure…