Related papers: TALUS: Reinforcing TEE Confidentiality with Crypto…
The logic of many protocols relies on time measurements. However, in Trusted Execution Environments (TEEs) like Intel SGX, the time source is outside the Trusted Computing Base: a malicious system hosting the TEE can manipulate that TEE's…
Future improvements in large language model (LLM) services increasingly hinge on access to high-value professional knowledge rather than more generic web data. However, the data providers of this knowledge face a skewed tradeoff between…
Federated Learning and Analytics (FLA) have seen widespread adoption by technology platforms for processing sensitive on-device data. However, basic FLA systems have privacy limitations: they do not necessarily require anonymization…
Intel SGX is known to be vulnerable to a class of practical attacks exploiting memory access pattern side-channels, notably page-fault attacks and cache timing attacks. A promising hardening scheme is to wrap applications in hardware…
Key-Value Stores (KVSs) are No-SQL databases that store data as key-value pairs and have gained popularity due to their simplicity, scalability, and fast retrieval capabilities. However, storing sensitive data in KVSs requires strong…
MapReduce is a programming model used extensively for parallel data processing in distributed environments. A wide range of algorithms were implemented using MapReduce, from simple tasks like sorting and searching up to complex clustering…
We aim to provide trusted time measurement mechanisms to applications and cloud infrastructure deployed in environments that could harbor potential adversaries, including the hardware infrastructure provider. Despite Trusted Execution…
In modern computer systems, user processes are isolated from each other by the operating system and the hardware. Additionally, in a cloud scenario it is crucial that the hypervisor isolates tenants from other tenants that are co-located on…
With the increasing popularity of cloud based machine learning (ML) techniques there comes a need for privacy and integrity guarantees for ML data. In addition, the significant scalability challenges faced by DRAM coupled with the high…
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…
Trusted Execution Environments (TEEs) provide hardware-enforced isolation that protects sensitive code and data from untrusted software. Despite their strong security guarantees, analyzing TEE applications remains challenging due to the…
Hardware-based Trusted Execution Environments (TEEs) are widely deployed in mobile devices. Yet their use has been limited primarily to applications developed by the device vendors. Recent standardization of TEE interfaces by GlobalPlatform…
Trusted-execution environments (TEE), like Intel SGX, isolate user-space applications into secure enclaves without trusting the OS. Thus, TEEs reduce the trusted computing base, but add one to two orders of magnitude slow-down. The…
Trusted Execution Environments (TEEs) are designed to protect the privacy and integrity of data in use. They enable secure data processing and sharing in peer-to-peer networks, such as vehicular ad hoc networks of autonomous vehicles,…
Fully Homomorphic Encryption (FHE) is one of the most promising technologies for privacy protection as it allows an arbitrary number of function computations over encrypted data. However, the computational cost of these FHE systems limits…
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,…
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…
Confidential computing has gained prominence due to the escalating volume of data-driven applications (e.g., machine learning and big data) and the acute desire for secure processing of sensitive data, particularly, across distributed…
The Virtual Machine (VM)-based Trusted-Execution-Environment (TEE) technology, like AMD Secure-Encrypted-Virtualization (SEV), enables the establishment of Confidential VMs (CVMs) to protect data privacy. But CVM lacks ways to provide the…
In TrustZone-assisted TEEs, the trusted OS has unrestricted access to both secure and normal world memory. Unfortunately, this architectural limitation has opened an aisle of exploration for attackers, which have demonstrated how to…