Trusted Execution Environments (TEEs) have been proposed as a solution to protect code confidentiality in scenarios where computation is outsourced to an untrusted operator. We study the resilience of such solutions to side-channel attacks in two commonly deployed scenarios: when a confidential code is a native binary that is shipped and executed within a TEE and when the confidential code is an intermediate representation (IR) executed on top of a runtime within a TEE. We show that executing IR code such as WASM bytecode on a runtime executing in a TEE leaks most IR instructions with high accuracy and therefore reveals the confidential code. Contrary to IR execution, native execution is much less susceptible to leakage and largely resists even the most powerful side-channel attacks. We evaluate native execution leakage in Intel SGX and AMD SEV and experimentally demonstrate end-to-end instruction extraction on Intel SGX, with WASM bytecode as IR executed within WAMR, a hybrid between a JIT compiler and interpreter developed by Intel. Our experiments show that IR code leakage from such systems is practical and therefore question the security claims of several commercial solutions which rely on TEEs+WASM for code confidentiality.
ODYSSEY: Reestablishing Confidentiality in Confidential Blockchain via Delegated Execution
Research Institute of Trustworthy Autonomous Systems（可信自主系统研究所）；Department of Computer Science and Engineering, Southern University of Science and Technology（南方科技大学计算机科学与工程系）；Ping An Technology (Shenzhen) Co., Ltd.（平安科技（深圳）有限公司）
Smart contracts are applications that execute on blockchains. Today they manage billions of dollars in value and motivate visionary plans for pervasive blockchain deployment. While smart contracts inherit the availability and other security assurances of blockchains, however, they are impeded by blockchains' lack of confidentiality and poor performance. We present Ekiden, a system that addresses these critical gaps by combining blockchains with Trusted Execution Environments (TEEs). Ekiden leverages a novel architecture that separates consensus from execution, enabling efficient TEE-backed con…
Trusted Execution Environments (TEEs) are rapidly emerging as a root-of-trust for protecting sensitive applications and data using hardware-backed isolated worlds of execution. TEEs provide robust assurances regarding critical algorithm execution, tamper-resistant credential storage, and platform integrity using remote attestation. However, the challenge of remotely managing credentials between TEEs remains largely unaddressed in existing literature. In this work, we present novel protocols using mutual attestation for supporting four aspects of secure remote credential management with TEEs: b…
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 (GP) promises to partially address this problem by enabling GP-compliant trusted applications to run on TEEs from different vendors. Nevertheless ordinary developers wishing to develop trusted applications face significant challenges. Access to hardware TEE interfaces are difficult to obtain without support from vendors. Tools and software needed to develop…
New types of Trusted Execution Environment (TEE) architectures like TrustLite and Intel Software Guard Extensions (SGX) are emerging. They bring new features that can lead to innovative security and privacy solutions. But each new TEE environment comes with its own set of interfaces and programming paradigms, thus raising the barrier for entry for developers who want to make use of these TEEs. In this paper, we motivate the need for realizing standard TEE interfaces on such emerging TEE architectures and show that this exercise is not straightforward. We report on our on-going work in mapping …
Federated learning allows us to distributively train a machine learning model where multiple parties share local model parameters without sharing private data. However, parameter exchange may still leak information. Several approaches have been proposed to overcome this, based on multi-party computation, fully homomorphic encryption, etc.; many of these protocols are slow and impractical for real-world use as they involve a large number of cryptographic operations. In this paper, we propose the use of Trusted Execution Environments (TEE), which provide a platform for isolated execution of code…
With the application of machine learning to security-critical and sensitive domains, there is a growing need for integrity and privacy in computation using accelerators, such as GPUs. Unfortunately, the support for trusted execution on GPUs is currently very limited - trusted execution on accelerators is particularly challenging since the attestation mechanism should not reduce performance. Although hardware support for trusted execution on GPUs is emerging, we study purely software-based approaches for trusted GPU execution. A software-only approach offers distinct advantages: (1) complement …
We investigate identity lease, a new type of service in which users lease their identities to third parties by providing them with full or restricted access to their online accounts or credentials. We discuss how identity lease could be abused to subvert the digital society, facilitating the spread of fake news and subverting electronic voting by enabling the sale of votes. We show that the emergence of Trusted Execution Environments and anonymous cryptocurrencies, for the first time, allows the implementation of such a lease service while guaranteeing fairness, plausible deniability and anony…
The need for data trading promotes the emergence of data market. However, in conventional data markets, both data buyers and data sellers have to use a centralized trading platform which might be dishonest. A dishonest centralized trading platform may steal and resell the data seller's data, or may refuse to send data after receiving payment from the data buyer. It seriously affects the fair data transaction and harm the interests of both parties to the transaction. To address this issue, we propose a novel blockchain-based data trading framework with Trusted Execution Environment (TEE) to pro…
With the rapid development of blockchain technology, different types of blockchains are adopted and interoperability across blockchains has received widespread attention. There have been many cross-chain solutions proposed in recent years, including notary scheme, sidechain, and relay chain. However, most of the existing platforms do not take confidentiality into account, although privacy has become an important concern for blockchain. In this paper, we present TrustCross, a privacy-preserving cross-chain platform to enable confidential interoperability across blockchains. The key insight behi…
Modern computer systems tend to rely on large trusted computing bases (TCBs) for operations. To address the TCB bloating problem, hardware vendors have developed mechanisms to enable or facilitate the creation of a trusted execution environment (TEE) in which critical software applications can execute securely in an isolated environment. Even under the circumstance that a host OS is compromised by an adversary, key security properties such as confidentiality and integrity of the software inside the TEEs can be guaranteed. The promise of integrity and security has driven developers to adopt it …
Blockchain protocols are inherently limited in transaction throughput and latency. Recent efforts to address performance and scale blockchains have focused on off-chain payment channels. While such channels can achieve low latency and high throughput, deploying them securely on top of the Bitcoin blockchain has been difficult, partly because building a secure implementation requires changes to the underlying protocol and the ecosystem. We present Teechan, a full-duplex payment channel framework that exploits trusted execution environments. Teechan can be deployed securely on the existing Bitco…
Modern multi-core processors share cache resources for maximum cache utilization and performance gains. However, this leaves the cache vulnerable to side-channel attacks, where timing differences in shared cache behavior are exploited to infer information on the victim's execution patterns, ultimately leaking private information. The root cause for these attacks is mutually distrusting processes sharing cache entries and accessing them in a deterministic manner. Various defenses against cache side-channel attacks have been proposed. However, they either degrade performance significantly, impos…
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 way for adoption in several sensitive application domains. This paper reviews existing remote attestation principles and compares the functionalities of current trusted execution environments as Intel SGX, Arm TrustZone and AMD SEV, as well as emerging RISC-V solutions.
Processing sensitive data, such as those produced by body sensors, on third-party untrusted clouds is particularly challenging without compromising the privacy of the users generating it. Typically, these sensors generate large quantities of continuous data in a streaming fashion. Such vast amount of data must be processed efficiently and securely, even under strong adversarial models. The recent introduction in the mass-market of consumer-grade processors with Trusted Execution Environments (TEEs), such as Intel SGX, paves the way to implement solutions that overcome less flexible approaches,…
Blockchain creates a secure environment on top of strict cryptographic assumptions and rigorous security proofs. It permits on-chain interactions to achieve trustworthy properties such as traceability, transparency, and accountability. However, current blockchain trustworthiness is only confined to on-chain, creating a "trust gap" to the physical, off-chain environment. This is due to the lack of a scheme that can truthfully reflect the physical world in a real-time and consistent manner. Such an absence hinders further real-world blockchain applications, especially for security-sensitive ones…
The majority of cloud providers offers users the possibility to deploy Trusted Execution Environments (TEEs) to protect their data and processes from high privileged adversaries. This offer is intended to address concerns of users when moving critical tasks into the cloud. However, TEEs only allow to attest the integrity of the environment at launch-time. To also enable the attestation of a TEE's integrity at run-time, we present GuaranTEE. GuaranTEE uses control-flow attestation to ensure the integrity of a service running within a TEE. By additionally placing all components of GuaranTEE in T…
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, paving the way for adoption in several sensitive application domains. This paper reviews remote attestation principles and explains how the modern and industrially well-established trusted execution environments Intel SGX, Arm TrustZone and AMD SEV, as well as emerging RISC-V solutions, leverage these mechanisms.
Trusted Execution Environments (TEEs) are used to protect sensitive data and run secure execution for security-critical applications, by providing an environment isolated from the rest of the system. However, over the last few years, TEEs have been proven weak, as either TEEs built upon security-oriented hardware extensions (e.g., Arm TrustZone) or resorting to dedicated secure elements were exploited multiple times. In this project, we introduce Trusted Execution Environments On-Demand (TEEOD), a novel TEE design that leverages the programmable logic (PL) in the heterogeneous system on chips …
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 host OS to use external resources such as storage, network, and other functions. Attackers may exploit this interface to leak data or corrupt the computation. We describe SGX-LKL, a system for running Linux binaries inside of Intel SGX enclaves that only exposes a minimal, protected and oblivious host interface: the interface is (i) minimal because SGX-LKL u…
Data privacy is unarguably of extreme importance. Nonetheless, there exist various daunting challenges to safe-guarding data privacy. These challenges stem from the fact that data owners have little control over their data once it has transgressed their local storage and been managed by third parties whose trustworthiness is questionable at times. Our work seeks to enhance data privacy by constructing a self-expiring data capsule. Sensitive data is encapsulated into a capsule which is associated with an access policy an expiring condition. The former indicates eligibility of functions that can…
Recently, cloud control systems have gained increasing attention from the research community as a solution to implement networked cyber-physical systems (CPSs). Such an architecture can reduce deployment and maintenance costs albeit at the expense of additional security and privacy concerns. In this paper, first, we discuss state-of-the-art security solutions for cloud control systems and their limitations. Then, we propose a novel control architecture based on Trusted Execution Environments (TEE). We show that such an approach can potentially address major security and privacy issues for clou…
This study identifies and proposes techniques to alleviate two key bottlenecks to executing deep neural networks in trusted execution environments (TEEs): page thrashing during the execution of convolutional layers and the decryption of large weight matrices in fully-connected layers. For the former, we propose a novel partitioning scheme, y-plane partitioning, designed to (i) provide consistent execution time when the layer output is large compared to the TEE secure memory; and (ii) significantly reduce the memory footprint of convolutional layers. For the latter, we leverage quantization and…
Privacy-Preserving Product-Quantized Approximate Nearest Neighbor Search Framework for Large-scale Datasets via A Hybrid of Fully Homomorphic Encryption and Trusted Execution Environment
Secure and trustworthy execution in heterogeneous SoCs is a major priority in the modern computing system. Security of SoCs mainly addresses two broad layers of trust issues: 1. Protection against hardware security threats(Side-channel, IP Privacy, Cloning, Fault Injection, and Denial of Service); and 2. Protection against malicious software attacks running on SoC processors. To resist malicious software-level attackers from gaining unauthorized access and compromising security, we propose a root of trust-based trusted execution mechanism \textbf{\textit{(named as \textbf{TrustToken}) }}. Trus…
The growing complexity of modern computing platforms and the need for strong isolation protections among their software components has led to the increased adoption of Trusted Execution Environments (TEEs). While several commercial and academic TEE architectures have emerged in recent times, they remain hard to compare and contrast. More generally, existing TEEs have not been subject to a holistic systematization to understand the available design alternatives for various aspects of TEE design and their corresponding pros-and-cons. Therefore, in this work, we analyze the design of existing TEE…
