Related papers: TEE-based Key-Value Stores: a Survey
In this paper, we present a comprehensive architecture for confidential computing, which we show to be general purpose and quite efficient. It executes the application as is, without any added burden or discipline requirements from the…
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…
During the last years, large-scale simulations of realistic physical environments which support the interaction of multiple participants over the Internet have become increasingly available and economically significant, most notably in the…
Protecting sensitive information in data-driven collaborations, such as AI training, while meeting the diverse requirements of multiple mutually distrusted stakeholders, is both crucial and challenging. This paper presents Styx, a novel…
Key-Value cache (\texttt{KV} \texttt{cache}) compression has emerged as a promising technique to optimize Large Language Model (LLM) serving. It primarily decreases the memory consumption of \texttt{KV} \texttt{cache} to reduce the…
Recent years have seen an increasing emphasis on information security, and various encryption methods have been proposed. However, for symmetric encryption methods, the well-known encryption techniques still rely on the key space to…
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…
Be it in the IoT or automotive domain, implicit certificates are gaining ever more prominence in constrained embedded devices. They present a resource-efficient security solution against common threat concerns. The computational…
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…
Trusted execution environment (TEE) technology has found many applications in mitigating various security risks in an efficient manner, which is attractive for critical infrastructure protection. First, the natural of critical…
Trusted execution environment (TEE) has provided an isolated and secure environment for building cloud-based analytic systems, but it still suffers from access pattern leakages caused by side-channel attacks. To better secure the data,…
Hardware-assisted trusted execution environments (TEEs) are critical building blocks of many modern applications. However, they have a one-way isolation model that introduces a semantic gap between a TEE and its outside world. This lack of…
Online services that desire to operate anonymously routinely host themselves as 'Hidden Services' in the Tor network. However, these services are frequently threatened by deanonymization attacks, whereby their IP address and location may be…
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,…
Remote mobile and embedded devices are used to deliver increasingly impactful services, such as medical rehabilitation and assistive technologies. Secure system logging is beneficial in these scenarios to aid audit and forensic…
When neural network model and data are outsourced to cloud server for inference, it is desired to preserve the confidentiality of model and data as the involved parties (i.e., cloud server, model providing client and data providing client)…
In our proposed work we mainly focus on data security of tenants so that only the authorized user can access the data. To provide this feature we use encryption and decryption process of data so that the only legal tenant can access their…
Our objective is to protect the integrity and confidentiality of applications operating in untrusted environments. Trusted Execution Environments (TEEs) are not a panacea. Hardware TEEs fail to protect applications against Sybil, Fork and…
Blockchains face inherent limitations when communicating outside their own ecosystem, largely due to the Byzantine Fault Tolerant (BFT) 3f+1 security model. Trusted Execution Environments (TEEs) are a promising mitigation because they allow…
Cloud key-value (KV) stores provide businesses with a cost-effective and adaptive alternative to traditional on-premise data management solutions. KV stores frequently consist of heterogeneous clusters, characterized by varying hardware…