When Blockchain Meets SGX: An Overview, Challenges, and Open Issues

The shielded computation of hardware-based trusted execution environments such as Intel Software Guard Extensions (SGX) can provide secure cloud computing on remote systems under untrusted privileged system software. However, hardware overheads for securing protected memory restrict its capacity to a modest size of several tens of megabytes, and more demands for protected memory beyond the limit cause costly demand paging. Although one of the widely used applications benefiting from the enhanced security of SGX, is the in-memory key-value store, its memory requirements are far larger than the protected memory limit. Furthermore, the main data structures commonly use fine-grained data items such as pointers and keys, which do not match well with the coarse-grained paging of the SGX memory extension technique. To overcome the memory restriction, this paper proposes a new in-memory key-value store designed for SGX with application-specific data security management. The proposed key-value store, called ShieldStore, maintains the main data structures in unprotected memory with each key-value pair individually encrypted and integrity-protected by its secure component running inside an enclave. Based on the enclave protection by SGX, ShieldStore provides secure data operations much more efficiently than the baseline SGX key-value store, achieving 8--11 times higher throughput with 1 thread, and 24--30 times higher throughput with 4 threads.

Intel Software Guard Extensions (SGX) is a promising hardware-based technology for protecting sensitive computation from potentially compromised system software. However, recent research has shown that SGX is vulnerable to branch-shadowing -- a side channel attack that leaks the fine-grained (branch granularity) control flow of an enclave (SGX protected code), potentially revealing sensitive data to the attacker. The previously-proposed defense mechanism, called Zigzagger, attempted to hide the control flow, but has been shown to be ineffective if the attacker can single-step through the enclave using the recent SGX-Step framework. Taking into account these stronger attacker capabilities, we propose a new defense against branch-shadowing, based on control flow randomization. Our scheme is inspired by Zigzagger, but provides quantifiable security guarantees with respect to a tunable security parameter. Specifically, we eliminate conditional branches and hide the targets of unconditional branches using a combination of compile-time modifications and run-time code randomization. We evaluated the performance of our approach using ten benchmarks from SGX-Nbench. Although we considered the worst-case scenario (whole program instrumentation), our results show that, on average, our approach results in less than 18% performance loss and less than 1.2 times code size increase.

Intel Software Guard Extensions (SGX) is a recent technology from Intel that makes it possible to execute security-critical parts of an application in a so-called SGX enclave, an isolated area of the system that is shielded from all other software (including the OS and/or hypervisor). SGX was designed with the objective of making it relatively straightforward to take a single module of an existing C application, and put that module in an enclave. The SGX SDK includes tooling to semi-automatically generate wrappers for an enclaved C module. The wrapped enclave can then easily be linked to the legacy application that uses the module.

Intel's Software Guard Extensions (SGX) are currently the most wide-spread commodity trusted execution environment, which provides integrity and confidentiality of sensitive code and data. Thereby, it offers protection even against privileged attackers and various forms of physical attacks. As a technology that only became available in late 2015, it has received massive interest and undergone a rapid evolution. Despite first ad-hoc attempts, there is so far no standardised approach to benchmark the SGX hardware, its associated environment, and techniques that were designed to harden SGX-based applications. In this paper, we present SGXoMeter, an open and modular framework designed to benchmark different SGX-aware CPUs, mcode revisions, SDK versions and extensions to mitigate side-channel attacks. SGXoMeter provides a set of practical SGX test case scenarios and eases the development of custom benchmarks. Furthermore, we compare it to sgx-nbench, the only other SGX application benchmark tool we are aware of, and evaluate their differences. Through our benchmark results, we identified a performance overhead of up to a10 times induced between two different SGX-SDK versions for certain workload scenarios.

This paper presents a comprehensive survey on the development of Intel SGX (software guard extensions) processors and its applications. With the advent of SGX in 2013 and its subsequent development, the corresponding research works are also increasing rapidly. In order to get a more comprehensive literature review related to SGX, we have made a systematic analysis of the related papers in this area. We first search through five large-scale paper retrieval libraries by keywords (i.e., ACM Digital Library, IEEE/IET Electronic Library, SpringerLink, Web of Science, and Elsevier Science Direct). We read and analyze a total of 128 SGX-related papers. The first round of extensive study is conducted to classify them. The second round of intensive study is carried out to complete a comprehensive analysis of the paper from various aspects. We start with the working environment of SGX and make a conclusive summary of trusted execution environment (TEE). We then focus on the applications of SGX. We also review and study multifarious attack methods to SGX framework and some recent security improvements made on SGX. Finally, we summarize the advantages and disadvantages of SGX with some future research opportunities. We hope this review could help the existing and future research works on SGX and its application for both developers and users.

SGX-LEGO: Fine-grained SGX controlled-channel attack and its countermeasure

Trusted execution as offered by Intel Software Guard Extensions (SGX) enables confidentiality and integrity for cloud-hosted services. While in principle all kinds of workloads can be secured using trusted execution, key-value stores have gained special attention as these services are an essential building block of most complex cloud deployments. So far the main design challenge has been to address current performance limitations of SGX. In addition, we identify the integration of SGX-guarded workloads with recent network technology, especially Remote Direct Memory Access (RDMA) as an upcoming requirement. RDMA allows fast direct access to remote memory at high bandwidth. However, SGX protected memory cannot be directly accessed over the network. Furthermore, due to the more powerful network, secured services might likely be CPU-bound as a result of the necessary cryptographic operations.

Trusted Execution Environment (TEE) is designed to deliver a safe execution environment for software systems. Intel Software Guard Extensions (SGX) provides isolated memory regions (i.e., SGX enclaves) to protect code and data from adversaries in the untrusted world. While existing research has proposed techniques to execute entire executable fles inside enclave instances by providing rich sets of OS facilities, one notable limitation of these techniques is the unavoidably large size of Trusted Computing Base (TCB), which can potentially break the principle of least privilege. In this work, we describe techniques that provide practical and efcient protection of security sensitive code components in legacy binary code. Our technique dissects input binaries into multiple components which are further built into SGX enclave instances. We also leverage deliberately-designed binary editing techniques to retroft the input binary code and preserve the original program semantics. Our tentative evaluations on hardening AES encryption and decryption procedures demonstrate the practicability and efciency of the proposed technique. © 2017 Association for Computing Machinery.

Threats to data processing in the cloud computing environment are increasing with emerging cloud applications. Intel Software Guard Extensions (SGX) implements a Trusted Execution Environment (TEE) through hardware-based isolation, which can enhance the security of cloud applications by providing a separate secure space that does not reveal its interior. A trusted memory area isolated by SGX, so-called enclave, protects the confidential code and data from any other software, including highly privileged system software. However, the adversary also benefits from isolation by inserting malicious code into the enclave where the system cannot detect it. Existing studies suggest various measures to deal with enclave malware, but these are based on an underlying assumption that the system must be trusted, which does not apply to the semi-honest cloud platform. To this end, we propose a novel method, named Interclave, that protects the system from enclave malware in the cloud computing environment without trusting any component other than the intermediate enclave. Interclave forces every ECALL and OCALL of a suspicious enclave to be executed through an intermediate enclave. This prevents the malicious behavior of enclave malware such as code-reuse attacks that modify the stack or register values associated with the program's execution address. Interclave stores and restores all stack and register values before and after the execution of the suspicious enclave, ensuring the integrity of these values. Our implementation is done with slight code modifications which occupy only a little storage capacity without complicated hardware changes.

With the extensive deployment and application of the Internet of Things (IoT), 5G and 6G technologies and edge intelligence, the volume of data generated by IoT and the number of intelligence applications derived from these data are rapidly growing. However, the absence of effective mechanisms to safeguard the vast data generated by IoT, along with the security and privacy of edge intelligence applications, hinders their further development and adoption. In recent years, Trusted Execution Environment (TEE) has emerged as a promising technology for securing cloud data storage and cloud processing, demonstrating significant potential for ensuring data and application confidentiality in more scenarios. Nevertheless, applying TEE technology to enhance security in IoT and edge intelligence scenarios still presents several challenges. This paper investigates the technical challenges faced by current TEE solutions, such as performance overhead and I/O security issues, in the context of the resource constraints and data mobility that are inherent to IoT and edge intelligence applications. Using Intel Software Guard Extensions (SGX) technology as a case study, this paper validates these challenges through extensive experiments. The results provide critical assessments and analyses essential for advancing the development and usage of TEE in IoT and edge intelligence scenarios.

In traditional centralized internet services, third parties authenticate the transactions of the users. An important property of decentralized blockchain networks is the unrestricted and secured access to the private keys of users, which may often be threatened for several reasons. One considerable problem in systems based on blockchain technology is when users lose access to their keys due to, e.g., a broken or lost device. This paper, firstly, introduces an implementation that generates and maintains the private key in an Intel Software Guard Extension (SGX) enclave. The implementation allows using the private key in a process isolated from all other processes running on the same system. Secondly, the paper provides a method that enables the secure storage and recovery of a back-up key to and from an external repository, using an end-to-end secure connection. One proposed application, with which this technology could be exploited, is the social wallet.

Due to the absence of in-enclave isolation, today's trusted execution environment (TEE), specifically Intel's Software Guard Extensions (SGX), does not have the capability to securely run different users' tasks within a single enclave, which is required for supporting real-world services, such as an in-enclave machine learning model that classifies the data from various sources, or a microservice (e.g., data search) that performs a very small task (within sub-seconds) for a user and therefore cannot afford the resources and the delay for creating a separate enclave for each user. To address this challenge, we developed Liveries, a technique that enables lightweight, verifiable in-enclave user isolation for protecting time-sharing services. Our approach restricts an in-enclave thread's privilege when configuring an enclave, and further performs integrity check and sanitization on critical enclave data upon user switches. For this purpose, we developed a novel technique that ensures the protection of sensitive user data (e.g., session keys) even in the presence of the adversary who may have compromised the enclave. Our study shows that the new technique is lightweight (1% overhead) and verifiable (about 3200 lines of code), making a step towards assured protection of real-world in-enclave services.

Cloud-based technologies play an increasing role in software engineering because of their scalability, availability, and cost efficiency. However, due to privacy issues, developers and organizations still hesitate to host applications that handle sensitive data on servers of external cloud providers. Modern hardware extensions, such as Intel's Software Guard Extensions (SGX), are an attempt to provide confidentiality and integrity for applications running on external hardware. Still, enabling SGX in cloud systems poses new challenges considering scalability and flexibility. In this paper, we propose an approach to address these issues by employing concepts from the domain of Dynamic Software Product Lines (DSPLs). We aim to enable applications running on SGX-based cloud systems to be securely reconfigurable and extendable during runtime. In particular, we describe properties that such an approach should fulfill and discuss corresponding challenges.

Users of modern data-processing services such as tax preparation or genomic screening are forced to trust them with data that the users wish to keep secret. Ryoan protects secret data while it is processed by services that the data owner does not trust. Accomplishing this goal in a distributed setting is difficult because the user has no control over the service providers or the computational platform. Confining code to prevent it from leaking secrets is notoriously difficult, but Ryoan benefits from new hardware and a request-oriented data model.Ryoan provides a distributed sandbox, leveraging hardware enclaves (e.g., Intel's software guard extensions (SGX) [15]) to protect sandbox instances from potentially malicious computing platforms. The protected sandbox instances confine untrusted data-processing modules to prevent leakage of the user's input data. Ryoan is designed for a request-oriented data model, where confined modules only process input once and do not persist state about the input. We present the design and prototype implementation of Ryoan and evaluate it on a series of challenging problems including email filtering, heath analysis, image processing and machine translation.

Malware attacks represent a significant part of today's security threats. Software guard extensions (SGX) are a set of hardware instructions introduced by Intel in their recent lines of processors that are intended to provide a secure execution environment for user-developed applications. To our knowledge, there was no serious attempt yet to overcome the SGX protection by leveraging the software supply chain infrastructure, such as weaknesses in the development, build or signing servers. While SGX protection does not specifically take into consideration such threats, we show in the current paper that a simple malware attack exploiting a separation between the build and signing processes can have a serious damaging impact, practically nullifying the SGX integrity protection measures. Finally, we also suggest some possible mitigations against the attack.