相关论文: TensorSCONE: A Secure TensorFlow Framework using I…

Encrypting data before sending it to the cloud protects it against hackers and malicious insiders, but requires the cloud to compute on encrypted data. Trusted (hardware) modules, e.g., secure enclaves like Intel's SGX, can very efficiently…

Intel(r) Software Guard Extensions (SGX) was originally released on client platforms and later extended to single socket server platforms. As developers have become familiar with the capabilities of the technology, the applicability of this…

Integrity is critical for maintaining system security, as it ensures that only genuine software is loaded onto a machine. Although confidential virtual machines (CVMs) function within isolated environments separate from the host, it is…

The big data industry is facing new challenges as concerns about privacy leakage soar. One of the remedies to privacy breach incidents is to encapsulate computations over sensitive data within hardware-assisted Trusted Execution…

Encrypted database systems provide a great method for protecting sensitive data in untrusted infrastructures. These systems are built using either special-purpose cryptographic algorithms that support operations over encrypted data, or by…

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), such as Intel's Software Guard Extensions (SGX), are increasingly being adopted to address trust and compliance issues in the public cloud. Intel SGX's second generation (SGXv2) addresses many…

Although cloud computing offers many advantages with regards to adaption of resources, we witness either a strong resistance or a very slow adoption to those new offerings. One reason for the resistance is that (i) many technologies such as…

Searchable encryption (SE) is one of the key enablers for building encrypted databases. It allows a cloud server to search over encrypted data without decryption. Dynamic SE additionally includes data addition and deletion operations to…

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…

Hardware support for trusted execution in modern CPUs enables tenants to shield their data processing workloads in otherwise untrusted cloud environments. Runtime systems for the trusted execution must rely on an interface to the untrusted…

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.…

Stream processing systems are important in modern applications in which data arrive continuously and need to be processed in real time. Because of their resource and scalability requirements, many of these systems run on the cloud, which is…

We present the SecureCloud EU Horizon 2020 project, whose goal is to enable new big data applications that use sensitive data in the cloud without compromising data security and privacy. For this, SecureCloud designs and develops a layered…

As an essential technology underpinning trusted computing, the trusted execution environment (TEE) allows one to launch computation tasks on both on- and off-premises data while assuring confidentiality and integrity. This article provides…

Cloud computing has emerged as a corner stone of today's computing landscape. More and more customers who outsource their infrastructure benefit from the manageability, scalability and cost saving that come with cloud computing. Those…

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…

Intel SGX provisions shielded executions for security-sensitive computation, but lacks support for trusted system services (TSS), such as clock, network and filesystem. This makes \textit{enclaves} vulnerable to Iago…

As machine learning (ML) technologies and applications are rapidly changing many computing domains, security issues associated with ML are also emerging. In the domain of systems security, many endeavors have been made to ensure ML model…

A number of trusted execution environments (TEEs) have been proposed by both academia and industry. However, most of them require specific hardware or firmware changes and are bound to specific hardware vendors (such as Intel, AMD, ARM, and…