Oblivious multi-party machine learning on trusted processors

Proceedings of the 25th USENIX Security Symposium

Volumn , Issue , 2016, Pages 619-636

  Ohrimenko, Olga ^a   Schuster, Felix ^a   Fournet, Cédric ^a   Mehta, Aastha ^a   Nowozin, Sebastian ^a   Vaswani, Kapil ^a   Costa, Manuel ^a  

^a MICROSOFT RESEARCH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

DATA ANALYTICS; DECISION TREES; FACTORIZATION; K-MEANS CLUSTERING; LARGE DATASET; MACHINE LEARNING; SUPPORT VECTOR MACHINES; TREES (MATHEMATICS);

ACCESS PATTERNS; DATA DEPENDENT; EFFICIENT IMPLEMENTATION; MATRIX FACTORIZATIONS; MULTI-PARTY COMPUTATION SCHEMES; MULTIPLE ORGANIZATIONS; ORDERS OF MAGNITUDE; PRIVACY PRESERVING;

LEARNING ALGORITHMS;

EID: 85068879161     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (71)

1. AJTAI, M., KOMLÓS, J., AND SZEMERÉDI, E. An O(nlogn) sorting network. In ACM Symposium on Theory of Computing (STOC) (1983).
2. ANATI, I., GUERON, S., JOHNSON, S., AND SCARLATA, V. Innovative technology for CPU based attestation and sealing. In Workshop on Hardware and Architectural Support for Security and Privacy (HASP) (2013).
3. ARASU, A., BLANAS, S., EGURO, K., KAUSHIK, R., KOSSMANN, D., RAMAMURTHY, R., AND VENKATESAN, R. Orthogonal security with Cipherbase. In Conference on Innovative Data Systems Research (CIDR) (2013).
4. ARASU, A., AND KAUSHIK, R. Oblivious query processing. In International Conference on Database Theory (ICDT) (2014).
5. BAJAJ, S., AND SION, R. TrustedDB: A trusted hardware-based database with privacy and data confidentiality. In IEEE Transactions on Knowledge and Data Engineering (2014).
6. BARNI, M., FAILLA, P., KOLESNIKOV, V., LAZZERETTI, R., SADEGHI, A., AND SCHNEIDER, T. Secure evaluation of private linear branching programs with medical applications. In European Symposium on Research in Computer Security (ESORICS) (2009).
7. BATCHER, K. E. Sorting networks and their applications. In Spring Joint Computer Conf. (1968).
8. BAUMANN, A., PEINADO, M., AND HUNT, G. Shielding applications from an untrusted cloud with Haven. In USENIX Symposium on Operating Systems Design and Implementation (OSDI) (2014).
9. BELL, R. M., AND KOREN, Y. Lessons from the Netflix prize challenge. ACM SIGKDD Explorations Newsletter 9, 2 (2007).
10. BISHOP, C. M. Neural networks for pattern recognition. Oxford university press, 1995.
11. BLUM, A., DWORK, C., MCSHERRY, F., AND NISSIM, K. Practical privacy: The SuLQ framework. In ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems (PODS) (2005).
12. BOSER, B. E., GUYON, I. M., AND VAPNIK, V. N. A training algorithm for optimal margin classifiers. In Proceedings of the fifth annual workshop on Computational learning theory (1992).
13. BOST, R., POPA, R. A., TU, S., AND GOLDWASSER, S. Machine learning classification over encrypted data. In Symposium on Network and Distributed System Security (NDSS) (2015).
14. BREIMAN, L. Random forests. Machine Learning 45, 1 (2001).
15. BREIMAN, L., FRIEDMAN, J. H., OLSHEN, R. A., AND STONE, C. J. Classification and Regression Trees. Wadsworth, 1984.
16. CRIMINISI, A., SHOTTON, J., AND KONUKOGLU, E. Decision forests: A unified framework for classification, regression, density estimation, manifold learning and semi-supervised learning. Foundations and Trends in Computer Graphics and Vision 7, 2-3 (2012).
17. C.YAO, A. Protocols for secure computations (extended abstract). In IEEE Symposium on Foundations of Computer Science (FOCS) (1982).
18. DE HOOGH, S., SCHOENMAKERS, B., CHEN, P., AND OP DEN AKKER, H. Practical secure decision tree learning in a teletreatment application. In Financial Cryptography and Data Security (FC) (2014).
19. DWORK, C., MCSHERRY, F., NISSIM, K., AND SMITH, A. Calibrating noise to sensitivity in private data analysis. In Theory of Cryptography Conference (TCC) (2006).
20. Fast CNN library. http://fastcnn.codeplex.com/ (accessed 17/02/2016).
21. FREDRIKSON, M., JHA, S., AND RISTENPART, T. Model inversion attacks that exploit confidence information and basic countermeasures. In ACM Conference on Computer and Communications Security (CCS) (2015).
22. FREDRIKSON, M., LANTZ, E., JHA, S., LIN, S., PAGE, D., AND RISTENPART, T. Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing. In USENIX Security Symposium (2014).
23. GENTRY, C. Fully homomorphic encryption using ideal lattices. In ACM Symposium on Theory of Computing (STOC) (2009).
24. GOLDREICH, O., MICALI, S., AND WIGDERSON, A. How to play any mental game. In ACM Symposium on Theory of Computing (STOC) (1987).
25. GOLDREICH, O., AND OSTROVSKY, R. Software protection and simulation on oblivious RAMs. Journal of the ACM (JACM) 43, 3 (1996).
26. GOODFELLOW, I., BENGIO, Y., AND COURVILLE, A. Deep learning. Book in preparation for MIT Press, 2016.
27. GRAEPEL, T., LAUTER, K., AND NAEHRIG, M. ML confidential: Machine learning on encrypted data. In International Conference on Information Security and Cryptology (ICISC) (2013).
28. HARPER, F. M., AND KONSTAN, J. A. The MovieLens datasets: History and context. In ACM Transactions on Interactive Intelligent Systems (TiiS) (2015).
29. HOEKSTRA, M., LAL, R., PAPPACHAN, P., ROZAS, C., PHEGADE, V., AND DEL CUVILLO, J. Using innovative instructions to create trustworthy software solutions. In Workshop on Hardware and Architectural Support for Security and Privacy (HASP) (2013).
30. HYEONG HONG, J., AND FITZGIBBON, A. Secrets of matrix factorization: Approximations, numerics, manifold optimization and random restarts. In Proceedings of the IEEE International Conference on Computer Vision (2015).
31. INTEL CORP. Intel 64 and IA-32 architectures software developer’s manual—combined volumes: 1, 2a, 2b, 2c, 3a, 3b and 3c, 2013. No. 325462-048.
32. KOREN, Y., BELL, R., AND VOLINSKY, C. Matrix factorization techniques for recommender systems. Computer, 8 (2009).
33. KUSHILEVITZ, E., LU, S., AND OSTROVSKY, R. On the (in)security of hash-based oblivious RAM and a new balancing scheme. In ACM-SIAM Symposium on Discrete Algorithms (SODA) (2012).
34. LAUR, S., LIPMAA, H., AND MIELIKÄINEN, T. Cryptographically private support vector machines. In ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (2006).
35. LINDELL, Y., AND PINKAS, B. Privacy preserving data mining. Journal of Cryptology (2000).
36. LINDELL, Y., AND PINKAS, B. Secure multiparty computation for privacy-preserving data mining. IACR Cryptology ePrint Archive (2008).
37. LIU, C., HARRIS, A., MAAS, M., HICKS, M. W., TIWARI, M., AND SHI, E. Ghostrider: A hardware-software system for memory trace oblivious computation. In International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) (2015).
38. LIU, C., WANG, X. S., NAYAK, K., HUANG, Y., AND SHI, E. ObliVM: A programming framework for secure computation. In IEEE Symposium on Security and Privacy (S&P) (2015).
39. LIU, F., YAROM, Y., GE, Q., HEISER, G., AND LEE, R. B. Last-level cache side-channel attacks are practical. In IEEE Symposium on Security and Privacy (S&P) (2015).
40. LLOYD, S. P. Least squares quantization in PCM’S. Bell Telephone Labs Memo (1957).
41. LLOYD, S. P. Least squares quantization in PCM. IEEE Transactions on Information Theory 28, 2 (1982).
42. LUK, C.-K., COHN, R., MUTH, R., PATIL, H., KLAUSER, A., LOWNEY, G., WALLACE, S., REDDI, V. J., AND HAZELWOOD, K. Pin: Building customized program analysis tools with dynamic instrumentation. In ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) (2005).
43. MACQUEEN, J. Some methods for classification and analysis of multivariate observations. In Berkeley Symposium on Mathematics, Statistics and Probability, Vol. 1 (1967).
44. MALKHI, D., NISAN, N., PINKAS, B., AND SELLA, Y. Fairplay: a secure two party computation system. In USENIX Security Symposium (2004).
45. MCKEEN, F., ALEXANDROVICH, I., BERENZON, A., ROZAS, C., SHAFI, H., SHANBHOGUE, V., AND SAVAGAONKAR, U. Innovative instructions and software model for isolated execution. In Workshop on Hardware and Architectural Support for Security and Privacy (HASP) (2013).
46. NARAYANAN, A., AND SHMATIKOV, V. Robust de-anonymization of large sparse datasets. In IEEE Symposium on Security and Privacy (S&P) (2008).
47. NAYAK, K., WANG, X. S., IOANNIDIS, S., WEINSBERG, U., TAFT, N., AND SHI, E. GraphSC: Parallel secure computation made easy. In IEEE Symposium on Security and Privacy (S&P) (2015).
48. NIKOLAENKO, V., IOANNIDIS, S., WEINSBERG, U., JOYE, M., TAFT, N., AND BONEH, D. Privacy-preserving matrix factorization. In ACM Conference on Computer and Communications Security (CCS) (2013).
49. OHRIMENKO, O., COSTA, M., FOURNET, C., GKANTSIDIES, C., KOHLWEISS, M., AND SHARMA, D. Observing and preventing leakage in MapReduce. In ACM Conference on Computer and Communications Security (CCS) (2015).
50. OHRIMENKO, O., GOODRICH, M. T., TAMASSIA, R., AND UPFAL, E. The Melbourne shuffle: Improving oblivious storage in the cloud. In International Colloquium on Automata, Languages and Programming (ICALP), vol. 8573. Springer, 2014.
51. QUINLAN, J. R. Induction of decision trees. Machine Learning 1, 1 (1986).
52. QUINLAN, J. R. C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993.
53. RANE, A., LIN, C., AND TIWARI, M. Raccoon: Closing digital side-channels through obfuscated execution. In USENIX Security Symposium (2015).
54. RASTOGI, A., HAMMER, M. A., AND HICKS, M. Wysteria: A programming language for generic, mixed-mode multiparty computations. In IEEE Symposium on Security and Privacy (S&P) (2014).
55. SARWAR, B., KARYPIS, G., KONSTAN, J., AND RIEDL, J. Application of dimensionality reduction in recommender system – A case study. Tech. rep., DTIC Document, 2000.
56. SCHÖLKOPF, B., AND SMOLA, A. J. Learning with kernels: support vector machines, regularization, optimization, and beyond. MIT press, 2002.
57. SCHUSTER, F., COSTA, M., FOURNET, C., GKANTSIDIS, C., PEINADO, M., MAINAR-RUIZ, G., AND RUSSINOVICH, M. VC3: Trustworthy data analytics in the cloud using sgx. In IEEE Symposium on Security and Privacy (S&P) (2015).
58. SHALEV-SHWARTZ, S., SINGER, Y., SREBRO, N., AND COTTER, A. Pegasos: Primal estimated sub-gradient solver for SVM. Mathematical programming 127, 1 (2011).
59. SHOKRI, R., AND SHMATIKOV, V. Privacy-preserving deep learning. In ACM Conference on Computer and Communications Security (CCS) (2015).
60. SINHA, R., COSTA, M., LAL, A., LOPES, N., SESHIA, S., RAJAMANI, S., AND VASWANI, K. A design and verification methodology for secure isolated regions. In ACM SIGPLAN Conference on Programming Language Design and Implementation (PLDI) (2016).
61. SMOLA, A. J., AND SCHÖLKOPF, B. A tutorial on support vector regression. Statistics and computing 14, 3 (2004).
62. STEFANOV, E., VAN DIJK, M., SHI, E., FLETCHER, C. W., REN, L., YU, X., AND DEVADAS, S. Path ORAM: an extremely simple oblivious RAM protocol. In ACM Conference on Computer and Communications Security (CCS) (2013).
63. TSOCHANTARIDIS, I., JOACHIMS, T., HOF-MANN, T., AND ALTUN, Y. Large margin methods for structured and interdependent output variables. In Journal of Machine Learning Research (2005).
64. TU, S., KAASHOEK, M. F., MADDEN, S., AND ZELDOVICH, N. Processing analytical queries over encrypted data. In International Conference on Very Large Data Bases (VLDB) (2013).
65. VAPNIK, V. N., AND VAPNIK, V. Statistical learning theory, vol. 1. Wiley New York, 1998.
66. WANG, X. S., NAYAK, K., LIU, C., CHAN, T., SHI, E., STEFANOV, E., AND HUANG, Y. Oblivious data structures. In ACM Conference on Computer and Communications Security (CCS) (2014).
67. WESTON, J., AND WATKINS, C. Support vector machines for multi-class pattern recognition. In ESANN (1999).
68. WU, D. J., FENG, T., NAEHRIG, M., AND LAUTER, K. Privately evaluating decision trees and random forests. IACR Cryptology ePrint Archive (2015).
69. XIE, P., BILENKO, M., FINLEY, T., GILADBACHRACH, R., LAUTER, K. E., AND NAEHRIG, M. Crypto-nets: Neural networks over encrypted data. CoRR abs/1412.6181 (2014).
70. XU, Y., CUI, W., AND PEINADO, M. Controlled-channel attacks: Deterministic side channels for untrusted operating systems. In IEEE Symposium on Security and Privacy (S&P) (2015).
71. YAO, A. C. How to generate and exchange secrets (extended abstract). In IEEE Symposium on Foundations of Computer Science (FOCS) (1986).