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1. Building GPU TEEs using CPU Secure Enclaves with GEVisor

   https://doi.org/10.1145/3620678.3624659  

   Wu, Xiaolong ; Tian, Dave Jing ; Kim, Chung Hwan ( October 2023 , ACM)

   Trusted execution environments (TEEs) have been proposed to protect GPU computation for machine learning applications operating on sensitive data. However, existing GPU TEE solutions either require CPU and/or GPU hardware modification to realize TEEs for GPUs, which prevents current systems from adopting them, or rely on untrusted system software such as GPU device drivers. In this paper, we propose using CPU secure enclaves, e.g., Intel SGX, to build GPU TEEs without modifications to existing hardware. To tackle the fundamental limitations of these enclaves, such as no support for I/O operations, we design and develop GEVisor, a formally verified security reference monitor software to enable a trusted I/O path between enclaves and GPU without trusting the GPU device driver. GEVisor operates in the Virtual Machine Extension (VMX) root mode, monitors the host system software to prevent unauthorized access to the GPU code and data outside the enclave, and isolates the enclave GPU context from other contexts during GPU computation. We implement and evaluate GEVisor on a commodity machine with an Intel SGX CPU and an NVIDIA Pascal GPU. Our experimental results show that our approach maintains an average overhead of 13.1% for deep learning and 18% for GPU benchmarks compared to native GPU computation while providing GPU TEEs for existing CPU and GPU hardware. 

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2. Detecting Privileged Side-Channel Attacks in Shielded Execution with Déjà Vu

   https://doi.org/10.1145/3052973.3053007  

   Chen, Sanchuan ; Zhang, Xiaokuan ; Reiter, Michael K. ; Zhang, Yinqian ( April 2017 , ACM Asia Conference on Computer & Communications Security 2017)

   Intel Software Guard Extension (SGX) protects the confidentiality and integrity of an unprivileged program running inside a secure enclave from a privileged attacker who has full control of the entire operating system (OS). Program execution inside this enclave is therefore referred to as shielded. Unfortunately, shielded execution does not protect programs from side-channel attacks by a privileged attacker. For instance, it has been shown that by changing page table entries of memory pages used by shielded execution, a malicious OS kernel could observe memory page accesses from the execution and hence infer a wide range of sensitive information about it. In fact, this page-fault side channel is only an instance of a category of side-channel attacks, here called privileged side-channel attacks, in which privileged attackers frequently preempt the shielded execution to obtain fine-grained side-channel observations. In this paper, we present Déjà Vu, a software framework that enables a shielded execution to detect such privileged side-channel attacks. Specifically, we build into shielded execution the ability to check program execution time at the granularity of paths in its control-flow graph. To provide a trustworthy source of time measurement, Déjà Vu implements a novel software reference clock that is protected by Intel Transactional Synchronization Extensions (TSX), a hardware implementation of transactional memory. Evaluations show that Déjà Vu effectively detects side-channel attacks against shielded execution and against the reference clock itself. 

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3. Securing Time in Untrusted Operating Systems with TimeSeal

   https://doi.org/10.1109/RTSS46320.2019.00018  

   Anwar, Fatima M. ; Garcia, Luis ; Han, Xi ; Srivastava, Mani ( December 2019 , 2019 IEEE Real-Time Systems Symposium (RTSS))

   null (Ed.)

   An accurate sense of elapsed time is essential for the safe and correct operation of hardware, software, and networked systems. Unfortunately, an adversary can manipulate the system's time and violate causality, consistency, and scheduling properties of underlying applications. Although cryptographic techniques are used to secure data, they cannot ensure time security as securing a time source is much more challenging, given that the result of inquiring time must be delivered in a timely fashion. In this paper, we first describe general attack vectors that can compromise a system's sense of time. To counter these attacks, we propose a secure time architecture, TIMESEAL that leverages a Trusted Execution Environment (TEE) to secure time-based primitives. While CPU security features of TEEs secure code and data in protected memory, we show that time sources available in TEE are still prone to OS attacks. TIMESEAL puts forward a high-resolution time source that protects against the OS delay and scheduling attacks. Our TIMESEAL prototype is based on Intel SGX and provides sub-millisecond (msec) resolution as compared to 1-second resolution of SGX trusted time. It also securely bounds the relative time accuracy to msec under OS attacks. In essence, TIMESEAL provides the capability of trusted timestamping and trusted scheduling to critical applications in the presence of a strong adversary. It delivers all temporal use cases pertinent to secure sensing, computing, and actuating in networked systems. 

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4. Komodo: Using verification to disentangle secure-enclave hardware from software

   https://doi.org/10.1145/3132747.3132782  

   Ferraiuolo, Andrew ; Baumann, Andrew ; Hawblitzel, Chris ; Parno, Bryan ( January 2017 , SOSP '17 Proceedings of the 26th Symposium on Operating Systems Principles)

   Intel SGX promises powerful security: an arbitrary number of user-mode enclaves protected against physical attacks and privileged software adversaries. However, to achieve this, Intel extended the x86 architecture with an isolation mechanism approaching the complexity of an OS microkernel, implemented by an inscrutable mix of silicon and microcode. While hardware-based security can offer performance and features that are difficult or impossible to achieve in pure software, hardware-only solutions are difficult to update, either to patch security flaws or introduce new features. Komodo illustrates an alternative approach to attested, on-demand, user-mode, concurrent isolated execution. We decouple the core hardware mechanisms such as memory encryption, address-space isolation and attestation from the management thereof, which Komodo delegates to a privileged software monitor that in turn implements enclaves. The monitor's correctness is ensured by a machine-checkable proof of both functional correctness and high-level security properties of enclave integrity and confidentiality. We show that the approach is practical and performant with a concrete implementation of a prototype in verified assembly code on ARM TrustZone. Our ultimate goal is to achieve security equivalent to or better than SGX while enabling deployment of new enclave features independently of CPU upgrades. The Komodo specification, prototype implementation, and proofs are available at https://github.com/Microsoft/Komodo. 

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5. Privacy-Preserving Localization using Enclaves

   https://doi.org/10.1109/UEMCON53757.2021.9666706  

   Khan, Arslan ; Choi, Joseph ; Tian, Dave ; Ward, Tyler ; Butler, Kevin ; Traynor, Patrick ; Shea, John ; Wong, Tan ( December 2021 , IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON’21))

   Localization is one form of cooperative spectrum sensing that lets multiple sensors work together to estimate the location of a target transmitter. However, the requisite exchange of spectrum measurements leads to exposure of the physical loca- tion of participating sensors. Furthermore, in some cases, a com- promised participant can reveal the sensitive characteristics of all participants. Accordingly, a lack of sufficient guarantees about data handling discourages such devices from working together. In this paper, we provide the missing data protections by processing spectrum measurements within attestable containers or enclaves. Enclaves provide runtime memory integrity and confidentiality using hardware extensions and have been used to secure various applications [1]–[8]. We use these enclave features as building blocks for new privacy-preserving particle filter protocols that minimize disruption of the spectrum sensing ecosystem. We then instantiate this enclave using ARM TrustZone and Intel SGX, and we show that enclave-based particle filter protocols incur minimal overhead (adding 16 milliseconds of processing to the measurement processing function when using SGX versus unprotected computation) and can be deployed on resource-constrained platforms that support TrustZone (incurring only a 1.01x increase in processing time when doubling particle count from 10,000 to 20,000), whereas cryptographically-based approaches suffer from multiple orders of magnitude higher costs. We effectively deploy enclaves in a distributed environment, dramatically improving current data handling techniques. To our best knowledge, this is the first work to demonstrate privacy-preserving localization in a multi-party environment with reasonable overhead. 

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