research-article

PixelVault: Using GPUs for Securing Cryptographic Operations

Authors:

Giorgos Vasiliadis,

Elias Athanasopoulos,

Michalis Polychronakis,

Sotiris IoannidisAuthors Info & Claims

CCS '14: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security

Pages 1131 - 1142

https://doi.org/10.1145/2660267.2660316

Published: 03 November 2014 Publication History

Abstract

Protecting the confidentiality of cryptographic keys in the event of partial or full system compromise is crucial for containing the impact of attacks. The Heartbleed vulnerability of April 2014, which allowed the remote leakage of secret keys from HTTPS web servers, is an indicative example. In this paper we present PixelVault, a system for keeping cryptographic keys and carrying out cryptographic operations exclusively on the GPU, which allows it to protect secret keys from leakage even in the event of full system compromise. This is possible by exposing secret keys only in GPU registers, keeping PixelVault's critical code in the GPU instruction cache, and preventing any access to both of them from the host. Due to the non-preemptive execution mode of the GPU, an adversary that has full control of the host cannot tamper with PixelVault's GPU code, but only terminate it, in which case all sensitive data is lost. We have implemented a PixelVault-enabled version of the OpenSSL library that allows the protection of existing applications with minimal modifications. Based on the results of our evaluation, PixelVault not only provides secure key storage using commodity hardware, but also significantly speeds up the processing throughput of cryptographic operations for server applications.

References

[1]

Benchmarking TPM-backed SSL. http://blog.habets.pp.se/2012/02/Benchmarking-TPMbacked-SSL.

[2]

CUDA Binary Utilities. http://docs.nvidia.com/cuda/cuda-binary-utilities/index.html.

[3]

Nouveau: Accelerated Open Source driver for nVidia cards. http://nouveau.freedesktop.org/.

[4]

NVIDIA Developer Forums - CUDA kernel timeout. https://devtalk.nvidia.com/default/topic/417276/cuda-kernel-timeout/.

[5]

OpenSSL Project. http://www.openssl.org/.

[6]

pscnv - PathScale NVIDIA graphics driver. https://github.com/pathscale/pscnv.

[7]

shinpei0208 / gdev. https://github.com/shinpei0208/gdev.

[8]

TCG PC Client Specific - TPM Interface Specification (TIS) Version 1.2. http://www.trustedcomputinggroup.org/files/resource_files/87BCE22B-1D09--3519-ADEBA772FBF02CBD/TCG_PCClientTPMSpecification_1--20_1-00_FINAL.pdf.

[9]

The Heartbleed Bug. http://heartbleed.com/.

[10]

Who holds the encryption keys? http://www.computerworld.com/s/article/9225414/Who_Holds_the_Keys_.

[11]

D. J. Bernstein. Cache-timing Attacks on AES, 2004.

[12]

E.-O. Blass and W. Robertson. TRESOR-HUNT: Attacking CPU-bound Encryption. In ACSAC, 2012.

Digital Library

[13]

D. Boneh, G. Durfee, and Y. Frankel. An Attack on RSA Given a Small Fraction of the Private Key Bits. In Lecture Notes in Computer Science, volume 1514 of Lecture Notes in Computer Science, pages 25--34. Springer, 1998.

Digital Library

[14]

D. Brumley and D. Boneh. Remote Timing Attacks are Practical. In USENIX Security, 2003.

Digital Library

[15]

D. Brumley and D. Song. Privtrans: Automatically Partitioning Programs for Privilege Separation. In USENIX Security, 2004.

Digital Library

[16]

X. Chen, T. Garfinkel, E. C. Lewis, P. Subrahmanyam, C. A. Waldspurger, D. Boneh, J. Dwoskin, and D. R. Ports. Overshadow: A Virtualization-based Approach to Retrofitting Protection in Commodity Operating Systems. In ASPLOS XIII, 2008.

Digital Library

[17]

D. Cook, R. Baratto, and A. Keromytis. Remotely Keyed Cryptographics Secure Remote Display Access Using (Mostly) Untrusted Hardware. In ICICS, 2005.

Digital Library

[18]

D. L. Cook, J. Ioannidis, A. D. Keromytis, and J. Luck. CryptoGraphics: Secret Key Cryptography Using Graphics Cards. In CT-RSA, 2005.

Digital Library

[19]

J. Daemen and V. Rijmen. AES Proposal: Rijndael, 1998.

[20]

Eliseo Hernandez. Accelerate Performance Using OpenCL with Intel HD Graphics. http://software.intel.com/en-us/articles/accelerateperformance-using-opencl-with-intel-hdgraphics.

[21]

B. Garmany and T. Müller. PRIME: Private RSA Infrastructure for Memory-less Encryption. In ACSAC, 2013.

Digital Library

[22]

D. Gullasch, E. Bangerter, and S. Krenn. Cache Games -- Bringing Access-Based Cache Attacks on AES to Practice. In IEEE S&P, 2011.

Digital Library

[23]

J. A. Halderman, S. D. Schoen, N. Heninger, W. Clarkson, W. Paul, J. A. Calandrino, A. J. Feldman, J. Appelbaum, and E. W. Felten. Lest We Remember: Cold-boot Attacks on Encryption Keys. Communications of the ACM, 52(5):91--98, 2009.

Digital Library

[24]

O. Harrison and J. Waldron. Practical Symmetric Key Cryptography on Modern Graphics Hardware. In USENIX Security, 2008.

Digital Library

[25]

O. Harrison and J. Waldron. Efficient Acceleration of Asymmetric Cryptography on Graphics Hardware. In AFRICACRYPT, 2009.

Digital Library

[26]

O. S. Hofmann, S. Kim, A. M. Dunn, M. Z. Lee, and E. Witchel. InkTag: Secure Applications on an Untrusted Operating System. In ASPLOS, 2013.

Digital Library

[27]

Intel. Software Guard Extensions Programming Reference. https://software.intel.com/sites/default/files/329298-001.pdf.

[28]

Y. Ishai, E. Kushilevitz, R. Ostrovsky, and A. Sahai. Cryptography with Constant Computational Overhead. In STOC, 2008.

Digital Library

[29]

J. Criswell, N. Dautenhahn, and V. Adve. Virtual Ghost: Protecting Applications from Hostile Operating Systems. In ASPLOS, 2014.

Digital Library

[30]

K. Jang, S. Han, S. Han, K. Park, and S. Moon. SSLShader: Cheap SSL Acceleration with Commodity Processors. In NSDI, 2011.

Digital Library

[31]

Jon Stokes. AMD reveals Fusion CPU+GPU, to challenge Intel in laptops. http://arstechnica.com/business/2010/02/amd-reveals-fusioncpugpu-to-challege-intel-in-laptops/.

[32]

S. Kato. Implementing Open-Source CUDA Runtime. 2013.

[33]

D. Kilpatrick. Privman: A Library for Partitioning Applications. In FREENIX, 2003.

[34]

C. Koc, T. Acar, and J. Kaliski, B.S. Analyzing and Comparing Montgomery Multiplication Algorithms. Micro, IEEE, 16(3):26--33, 1996.

Digital Library

[35]

P. C. Kocher. Timing Attacks on Implementations of Diffie-Hellman, RSA, DSS, and Other Systems. In CRYPTO'96, 1996.

Digital Library

[36]

Luitjens, Justin and Rennich, Steven. CUDA Warps and Occupancy. http://on-demand.gputechconf.com/gtc-express/2011/presentations/cuda_webinars_WarpsAndOccupancy.pdf, 2011.

[37]

C. Maurice, C. Neumann, O. Heen, and A. Francillon. Confidentiality Issues on a GPU in a Virtualized Environment. In FC, 2014.

[38]

K. Menychtas, K. Shen, and M. L. Scott. Enabling OS Research by Inferring Interactions in the Black-box GPU Stack. In USENIX ATC, 2013.

Digital Library

[39]

P. Micikevicius. Local Memory and Register Spilling. http://on-demand.gputechconf.com/gtcexpress/2011/presentations/register_spilling.pdf.

[40]

T. Müller, A. Dewald, and F. C. Freiling. AESSE: A Cold-boot Resistant Implementation of AES. In EuroSec, 2010.

Digital Library

[41]

T. Müller, F. C. Freiling, and A. Dewald. TRESOR Runs Encryption Securely Outside RAM. In USENIX Security, 2011.

Digital Library

[42]

NVIDIA. CUDA Programming Guide, version 4.0. http://developer.download.nvidia.com/compute/cuda/4_0/toolkit/docs/CUDA_C_Programming_Guide.pdf.

[43]

NVIDIA. Dynamic Parallelism in CUDA. http://developer.download.nvidia.com/assets/cuda/files/CUDADownloads/TechBrief_Dynamic_Parallelism_in_CUDA.pdf.

[44]

NVIDIA. Next Generation CUDA Compute Architecture: Fermi. http://www.nvidia.com/content/PDF/fermi_white_papers/NVIDIA_Fermi_Compute_Architecture_Whitepaper.pdf.

[45]

NVIDIA. NVIDIA's Next Generation CUDA Compute Architecture: Kepler GK110. http://www.nvidia.com/content/PDF/kepler/NVIDIA-Kepler-GK110-Architecture-Whitepaper.pdf.

[46]

NVIDIA Developer Zone. Flushing Instruction Cache on GPU. https://devtalk.nvidia.com/default/topic/467841/flushing-instruction-cacheon-gpu/.

[47]

NVIDIA Developer Zone. PTX ISA :: CUDA Toolkit Documentation. http://docs.nvidia.com/cuda/ parallel-thread-execution/index.html.

[48]

D. R. Piegdon and L. Pimenidis. Targeting Physically Addressable Memory. In DIMVA, 2007.

Digital Library

[49]

R. D. Pietro, F. Lombardi, and A. Villani. CUDA Leaks: Information Leakage in GPU Architectures. ArXiv, May 2013.

[50]

N. Provos, M. Friedl, and P. Honeyman. Preventing Privilege Escalation. In USENIX Security, 2003.

Digital Library

[51]

R. L. Rivest, A. Shamir, and L. Adleman. A Method for Obtaining Digital Signatures and Public-key Cryptosystems. Communications of ACM, 21, February 1978.

Digital Library

[52]

C. J. Rossbach, J. Currey, M. Silberstein, B. Ray, and E. Witchel. PTask: Operating System Abstractions to Manage GPUs as Compute Devices. In SOSP, 2011.

Digital Library

[53]

A. Shamir and N. v. Someren. Playing "Hide and Seek" with Stored Keys. In FC, 1999.

Digital Library

[54]

U. Shankar and D. Wagner. Preventing Secret Leakage from fork(): Securing Privilege-Separated Applications. In ICC, 2006.

[55]

M. Silberstein, B. Ford, I. Keidar, and E. Witchel. GPUfs: Integrating a File System with GPUs. In ASPLOS, 2013.

Digital Library

[56]

P. Simmons. Security through Amnesia: A Software-based Solution to the Cold-boot Attack on Disk Encryption. Technical report, 2011.

[57]

P. Stewin and I. Bystrov. Understanding DMA Malware. In DIMVA, 2013.

Digital Library

[58]

R. Szerwinski and T. Güneysu. Exploiting the Power of GPUs for Asymmetric Cryptography. In CHES, 2008.

Digital Library

[59]

E. Tromer, D. A. Osvik, and A. Shamir. Efficient Cache Attacks on AES, and Countermeasures. Journal of Cryptology, 23, 2010.

Digital Library

[60]

G. Vasiliadis, L. Koromilas, M. Polychronakis, and S. Ioannidis. GASPP: A GPU-Accelerated Stateful Packet Processing Framework. In USENIX ATC, 2014.

Digital Library

[61]

G. Vasiliadis, M. Polychronakis, and S. Ioannidis. MIDeA: A Multi-Parallel Intrusion Detection Architecture. In CCS, 2011.

Digital Library

[62]

H. Wong, M.-M. Papadopoulou, M. Sadooghi-Alvandi, and A. Moshovos. Demystifying GPU Microarchitecture through Microbenchmarking. In ISPASS, 2010.

Cited By

Christou GVasiliadis GZarras AIoannidis S(2025)iVault: Architectural Code Concealing Techniques to Protect Cryptographic KeysEmbedded Computer Systems: Architectures, Modeling, and Simulation10.1007/978-3-031-78380-7_13(152-164)Online publication date: 28-Jan-2025
https://doi.org/10.1007/978-3-031-78380-7_13
Lim HKim JLee HLuo BLiao XXu JKirda ELie D(2024)uMMU: Securing Data Confidentiality with Unobservable Memory SubsystemProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security10.1145/3658644.3690340(2993-3007)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3658644.3690340
Sekar GJoseph MBalasubramanian R(2024)Fault-assisted side-channel analysis of HMAC-StreebogCryptologia10.1080/01611194.2024.232854849:2(153-169)Online publication date: 14-Apr-2024
https://doi.org/10.1080/01611194.2024.2328548
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Index Terms

PixelVault: Using GPUs for Securing Cryptographic Operations

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Published In

cover image ACM Conferences

CCS '14: Proceedings of the 2014 ACM SIGSAC Conference on Computer and Communications Security

November 2014

1592 pages

ISBN:9781450329576

DOI:10.1145/2660267

General Chair:
Gail-Joon Ahn
Arizona State University, USA
,
Program Chairs:
Moti Yung
Google -- Columbia University, USA
,
Ninghui Li
Purdue University, USA

Copyright © 2014 ACM.

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Published: 03 November 2014

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CCS'14: 2014 ACM SIGSAC Conference on Computer and Communications Security

November 3 - 7, 2014

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CCS '14 Paper Acceptance Rate 114 of 585 submissions, 19%;

Overall Acceptance Rate 1,261 of 6,999 submissions, 18%

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Cited By

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https://doi.org/10.1007/978-3-031-78380-7_13
Lim HKim JLee HLuo BLiao XXu JKirda ELie D(2024)uMMU: Securing Data Confidentiality with Unobservable Memory SubsystemProceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security10.1145/3658644.3690340(2993-3007)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3658644.3690340
Sekar GJoseph MBalasubramanian R(2024)Fault-assisted side-channel analysis of HMAC-StreebogCryptologia10.1080/01611194.2024.232854849:2(153-169)Online publication date: 14-Apr-2024
https://doi.org/10.1080/01611194.2024.2328548
Lee HSong CKang B(2023)Harnessing the x86 Intermediate Rings for Intra-Process IsolationIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2022.319252420:4(3251-3268)Online publication date: 1-Jul-2023
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Li CGuan LLin JLuo BCai QJing JWang J(2021)Mimosa: Protecting Private Keys Against Memory Disclosure Attacks Using Hardware Transactional MemoryIEEE Transactions on Dependable and Secure Computing10.1109/TDSC.2019.289766618:3(1196-1213)Online publication date: 1-May-2021
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Hunt TJia ZMiller VSzekely AHu YRossbach CWitchel EBhagwan RPorter G(2020)TelekineProceedings of the 17th Usenix Conference on Networked Systems Design and Implementation10.5555/3388242.3388301(817-834)Online publication date: 25-Feb-2020
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