Related papers: End-to-End Security for Distributed Event-Driven E…
We present a practical framework to deploy privacy-preserving machine learning (PPML) applications in untrusted clouds based on a trusted execution environment (TEE). Specifically, we shield unmodified PyTorch ML applications by running…
Attestation is a fundamental building block to establish trust over software systems. When used in conjunction with trusted execution environments, it guarantees the genuineness of the code executed against powerful attackers and threats,…
Edge computing promises to reshape the centralized nature of today's cloud-based applications by bringing computing resources, at least in part, closer to the user. Reasons include the increasing need for real-time (short-delay,…
We present DarkneTZ, a framework that uses an edge device's Trusted Execution Environment (TEE) in conjunction with model partitioning to limit the attack surface against Deep Neural Networks (DNNs). Increasingly, edge devices (smartphones…
Entropy--a measure of randomness--is compulsory for the generation of secure cryptographic keys; however, Internet of Things (IoT) devices that are small or constrained often struggle to collect suf ficient entropy. In this article, we…
Enclave deployments often fail to simultaneously be secure (e.g., resistant to side channel attacks), powerful (i.e., as fast as an off-the-shelf server), and flexible (i.e., unconstrained by development hurdles). In this paper, we present…
Embedded devices face an ever-expanding threat landscape: vulnerabilities in application software, operating system kernels, and peripherals threaten the embedded device integrity. Existing computer-architectural defenses fully consider at…
The blockchain-based smart contract lacks privacy since the contract state and instruction code are exposed to the public. Combining smart-contract execution with Trusted Execution Environments (TEEs) provides an efficient solution, called…
Extreme edge computing (EEC) refers to the endmost part of edge computing wherein computational tasks and edge services are deployed only on extreme edge devices (EEDs). EEDs are consumer or user-owned devices that offer computational…
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,…
Blockchain technology promises to revolutionize manufacturing industries. For example, several supply-chain use-cases may benefit from transparent asset tracking and automated processes using smart contracts. Several real-world deployments…
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…
Application size and complexity are the underlying cause of numerous security vulnerabilities in code. In order to mitigate the risks arising from such vulnerabilities, various techniques have been proposed to isolate the execution of…
Trusted execution environments (TEE) such as Intel's Software Guard Extension (SGX) have been widely studied to boost security and privacy protection for the computation of sensitive data such as human genomics. However, a performance…
Foundation Models (FMs) display exceptional performance in tasks such as natural language processing and are being applied across a growing range of disciplines. Although typically trained on large public datasets, FMs are often fine-tuned…
Attestation is a fundamental building block to establish trust over software systems. When used in conjunction with trusted execution environments, it guarantees that genuine code is executed even when facing strong attackers, paving the…
Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose…
The distributed (federated) LLM is an important method for co-training the domain-specific LLM using siloed data. However, maliciously stealing model parameters and data from the server or client side has become an urgent problem to be…
We present Airtnt, a novel scheme that enables users with CPUs that support Trusted Execution Environments (TEEs) and remote attestation to rent out computing time on secure enclaves to untrusted users. Airtnt makes use of the attestation…
Enforcing integrity and confidentiality of users' application code and data is a challenging mission that any software developer working on an online production grade service is facing. Since cryptology is not a widely understood subject,…