Related papers: CCxTrust: Confidential Computing Platform Based on…
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…
Trusted Execution Environments (TEEs), such as Intel SGX and ARM TrustZone, provide isolated regions of CPU and memory for secure computation and are increasingly used to protect sensitive data and code across diverse application domains.…
Trusted Execution Environments (TEEs), such as Intel Software Guard eXtensions (SGX), are considered as a promising approach to resolve security challenges in clouds. TEEs protect the confidentiality and integrity of application code and…
Federated Learning (FL) is a distributed machine learning approach that has emerged as an effective way to address recent privacy concerns. However, FL introduces the need for additional security measures as FL alone is still subject to…
In this paper, we propose a new secure machine learning inference platform assisted by a small dedicated security processor, which will be easier to protect and deploy compared to today's TEEs integrated into high-performance processors.…
This paper addresses privacy protection in decentralized Artificial Intelligence (AI) using Confidential Computing (CC) within the Atoma Network, a decentralized AI platform designed for the Web3 domain. Decentralized AI distributes AI…
Machine learning has become a critical component of modern data-driven online services. Typically, the training phase of machine learning techniques requires to process large-scale datasets which may contain private and sensitive…
Automated verification of security protocols based on dynamic root of trust, typically relying on protected hardware such as TPM, involves several challenges that we address in this paper. We model the semantics of trusted computing…
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…
Decentralized smart contracts enable trustless collaboration but suffer from limited privacy and scalability, which hinders broader adoption. Trusted Execution Environment (TEE) based off-chain execution frameworks offer a promising…
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…
Confidential computing protects data in use within Trusted Execution Environments (TEEs), but current TEEs provide little support for secure communication between components. As a result, pipelines of independently developed and deployed…
Intel Trust Domain Extensions (TDX) is a new architectural extension in the 4th Generation Intel Xeon Scalable Processor that supports confidential computing. TDX allows the deployment of virtual machines in the Secure-Arbitration Mode…
Trusted Platform Modules (TPMs), which serve as the root of trust in secure systems, are secure crypto-processors that carry out cryptographic primitives. Should large-scale quantum computing become a reality, the cryptographic primitives…
Confidential containers protect cloud-native workloads using trusted execution environments (TEEs). However, existing Container-in-TEE designs (e.g., Confidential Containers (CoCo)) encapsulate the entire runtime within the TEE, inflating…
Trusted Execution Environments (TEEs) are hardware-enforced memory isolation units, emerging as a pivotal security solution for security-critical applications. TEEs, like Intel SGX and ARM TrustZone, allow the isolation of confidential code…
Trusted execution environments (TEEs) protect the integrity and confidentiality of running code and its associated data. Nevertheless, TEEs' integrity protection does not extend to the state saved on disk. Furthermore, modern cloud-native…
The ongoing trend of moving data and computation to the cloud is met with concerns regarding privacy and protection of intellectual property. Cloud Service Providers (CSP) must be fully trusted to not tamper with or disclose processed data,…
Confidential computing is a key technology for isolating high-assurance applications from the large amounts of untrusted code typical in modern systems. Existing confidential computing systems cannot be certified for use in critical…
Confidential computing plays an important role in isolating sensitive applications from the vast amount of untrusted code commonly found in the modern cloud. We argue that it can also be leveraged to build safer and more secure…