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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…
Cloud business intelligence is an increasingly popular choice to deliver decision support capabilities via elastic, pay-per-use resources. However, data security issues are one of the top concerns when dealing with sensitive data. In this…
While the security of the cloud remains a concern, a common practice is to encrypt data before outsourcing them for utilization. One key challenging issue is how to efficiently perform queries over the ciphertext. Conventional crypto-based…
Using public cloud services for storing and sharing confidential data requires end users to cryptographically protect both the data and the access to the data. In some cases, the identity of end users needs to remain confidential against…
Nowadays companies are increasingly adopting the technology ofcloud computing. This technology is subject to a lot of research and continuousadvances are made. The use of cloud computing in the companies advantagessuch as: reducing costs,…
Cloud computing is an Internet-based computing, where shared resources, software and information, are provided to computers and devices on-demand. It provides people the way to share distributed resources and services that belong to…
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) 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…
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…
We often interact with untrusted parties. Prioritization of privacy can limit the effectiveness of these interactions, as achieving certain goals necessitates sharing private data. Traditionally, addressing this challenge has involved…
The use of trusted hardware has become a promising solution to enable privacy-preserving machine learning. In particular, users can upload their private data and models to a hardware-enforced trusted execution environment (e.g. an enclave…
Trusted execution environments (TEEs) are an integral part of modern secure processors. They ensure that their application and code pages are confidential, tamper proof and immune to diverse types of attacks. In 2021, Intel suddenly…
This paper shows that cache-based optimizations are often ineffective in cloud virtual machines (VMs) due to limited visibility into and control over provisioned caches. In public clouds, CPU caches can be partitioned or shared among VMs,…
Encrypted databases have been studied for more than 10 years and are quickly emerging as a critical technology for the cloud. The current state of the art is to use property-preserving encrypting techniques (e.g., deterministic encryption)…
In order to determine the user's trust is a growing concern for ensuring privacy and security in a cloud computing environment. In cloud, user's data is stored in one or more remote server(s) which poses more security challenges for the…
Virtualization enables information and communications technology industry to better manage computing resources. In this regard, improvements in virtualization approaches together with the need for consistent runtime environment, lower…
Trusted Execution Environments (TEEs) are gradually adopted by major cloud providers, offering a practical option of \emph{confidential computing} for users who don't fully trust public clouds. TEEs use CPU-enabled hardware features to…
Authentication proxies, which store users' secret credentials and submit them to servers on their behalf, offer benefits with respect to security of the authentication and usability of credential management. However, as being a service that…
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…
Applications running in Trusted Execution Environments (TEEs) commonly use untrusted external services such as host File System. Adversaries may maliciously alter the normal service behavior to trigger subtle application bugs that would…