Related papers: WELES: Policy-driven Runtime Integrity Enforcement…
Platforms are nowadays typically equipped with tristed execution environments (TEES), such as Intel SGX and ARM TrustZone. However, recent microarchitectural attacks on TEEs repeatedly broke their confidentiality guarantees, including the…
In the automotive security sector, the absence of a testing platform that is configurable, practical, and user-friendly presents considerable challenges. These difficulties are compounded by the intricate design of vehicle systems, the…
CaMeL (Capabilities for Machine Learning) introduces a capability-based sandbox to mitigate prompt injection attacks in large language model (LLM) agents. While effective, CaMeL assumes a trusted user prompt, omits side-channel concerns,…
Recently, cloud control systems have gained increasing attention from the research community as a solution to implement networked cyber-physical systems (CPSs). Such an architecture can reduce deployment and maintenance costs albeit at the…
Ensuring robustness in ML-enabled software systems requires addressing critical challenges, such as silent failures, out-of-distribution (OOD) data, and adversarial attacks. Traditional software engineering practices, which rely on…
Recent years have seen smart contracts are getting increasingly popular in building trustworthy decentralized applications. Previous research has proposed static and dynamic techniques to detect vulnerabilities in smart contracts. These…
A niche corner of the Web3 world is increasingly making use of hardware-based Trusted Execution Environments (TEEs) to build decentralized infrastructure. One of the motivations to use TEEs is to go beyond the current performance…
In-host shared memory (IVSHMEM) enables high-throughput, zero-copy communication between virtual machines, but today's implementations lack any security control, allowing any application to eavesdrop or tamper with the IVSHMEM region. This…
Hardware Security Modules (HSMs) are trusted machines that perform sensitive operations in critical ecosystems. They are usually required by law in financial and government digital services. The most important feature of an HSM is its…
A high-resolution video surveillance management system incurs huge amounts of storage and network bandwidth. The current infrastructure required to support a high resolution video surveillance management system (VMS) is expensive and time…
Verifying hardware designs in embedded systems is crucial but often labor-intensive and time-consuming. While existing solutions have improved automation, they frequently rely on unrealistic assumptions. To address these challenges, we…
We propose VAMS, a system that enables transparency for audits of access to data requests without compromising the privacy of parties in the system. VAMS supports audits on an aggregate level and an individual level, by relying on three…
Fair machine learning is a thriving and vibrant research topic. In this paper, we propose Fairness as a Service (FaaS), a secure, verifiable and privacy-preserving protocol to computes and verify the fairness of any machine learning (ML)…
WebAssemly is an emerging runtime for Web applications and has been supported in almost all browsers. Recently, WebAssembly is further regarded to be a the next-generation environment for blockchain applications, and has been adopted by…
The emergence of cloud computing presents a strategic direction for critical infrastructures and promises to have far-reaching effects on their systems and networks to deliver better outcomes to the nations at a lower cost. However, when…
As the frequency of cyber threats increases, conventional penetration testing is failing to capture the entirety of todays complex environments. To solve this problem, we propose the Vulnerability Mitigation System (VMS), a novel agent…
Modern network virtualization platforms enable users to specify custom topologies and arbitrary addressing schemes for their virtual networks. These platforms have, however, been targeting the data center of a single provider, which is…
A growing framework of legal and ethical requirements limit scientific and commercial evalua-tion of personal data. Typically, pseudonymization, encryption, or methods of distributed com-puting try to protect individual privacy. However,…
MLaaS (Machine Learning as a Service) has become popular in the cloud computing domain, allowing users to leverage cloud resources for running private inference of ML models on their data. However, ensuring user input privacy and secure…
Process attestation systems verify that a continuous physical process, such as human authorship, actually occurred, rather than merely checking system state. These systems face a fundamental dependability challenge: the evidence collection…