Related papers: Characterizing Trust Boundary Vulnerabilities in T…

This research focuses on transforming CVEs to hands-on educational lab for cybersecurity training. The study shows the practical application of CVEs by developing containerized lab environments- Docker to simulate real-world vulnerabilities…

Verifying the private liquidity state of Lightning Network (LN) channels is desirable for auditors, service providers, and network participants who need assurance of financial capacity. Current methods often lack robustness against a…

Trusted execution environments (TEEs) offer hardware-assisted means to protect code and data. However, as shown in numerous results over the years, attackers can use side-channels to leak data access patterns and even single-step the code.…

RISC-V-based Trusted Execution Environments (TEEs) are gaining traction in the automotive and IoT sectors as a foundation for protecting sensitive computations. However, the supporting infrastructure around these TEEs remains immature. In…

Autonomous and robotic systems are increasingly being trusted with sensitive activities with potentially serious consequences if that trust is broken. Runtime verification techniques present a natural source of inspiration for monitoring…

Threat modelling is foundational to secure systems engineering and should be done in consideration of the context within which systems operate. On the other hand, the continuous evolution of both the technical sophistication of threats and…

Data-driven intelligent applications in modern online services have become ubiquitous. These applications are usually hosted in the untrusted cloud computing infrastructure. This poses significant security risks since these applications…

Cloud workloads combine software components from different parties to process sensitive data. Each component has its own trust model - it must protect its assets from the rest of the system, yet share sensitive data with components it…

Edge intelligence enables resource-demanding Deep Neural Network (DNN) inference without transferring original data, addressing concerns about data privacy in consumer Internet of Things (IoT) devices. For privacy-sensitive applications,…

Security in TrustZone-enabled heterogeneous system-on-chip (SoC) is gaining increasing attention for several years. Mainly because this type of SoC can be found in more and more applications in servers or in the cloud. The inside-SoC…

This review discusses the theoretical frameworks and application prospects of Zero Trust Security (ZTS) in cloud computing context. This is because, as organisations move more of their applications and data to the cloud, the old…

Modern cloud computing platforms based on virtual machine monitors carry a variety of complex business that present many network security vulnerabilities. At present, the traditional architecture employs a number of security devices at…

Today's cloud vendors are competing to provide various offerings to simplify and accelerate AI service deployment. However, cloud users always have concerns about the confidentiality of their runtime data, which are supposed to be processed…

The increasing adoption of Large Language Models (LLMs) in cloud environments raises critical security concerns, particularly regarding model confidentiality and data privacy. Confidential computing, enabled by Trusted Execution…

Data theft and leakage, caused by external adversaries and insiders, demonstrate the need for protecting user data. Trusted Execution Environments (TEEs) offer a promising solution by creating secure environments that protect data and code…

Constructing a Trusted Execution Environment (TEE) on Field Programmable Gate Array System on Chip (FPGA-SoC) in Cloud can effectively protect users' private intel-lectual Property (IP) cores. In order to facilitate the wide-spread…

Large Language Models (LLMs) deployed on mobile devices offer benefits like user privacy and reduced network latency, but introduce a significant security risk: the leakage of proprietary models to end users. To mitigate this risk, we…

Heterogeneous computing, which incorporates GPUs, NPUs, and FPGAs, is increasingly utilized to improve the efficiency of computer systems. However, this shift has given rise to significant security and privacy concerns, especially when the…

Integrity is critical for maintaining system security, as it ensures that only genuine software is loaded onto a machine. Although confidential virtual machines (CVMs) function within isolated environments separate from the host, it is…

Confidential computing safeguards sensitive computations from untrusted clouds, with Confidential Virtual Machines (CVMs) providing a secure environment for guest OS. However, CVMs often come with large and vulnerable operating system…