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Article title A GENERAL MODEL OF CRYPTOGRAPHICALLY SECURE COMPUTING SYSTEM
Authors L.K. Babenko, Ph.B. Burtyka, O.B. Makarevich, A.V. Trepacheva
Section SECTION III. CRYPTOGRAPHIC PROTECTION OF INFORMATION
Month, Year 05, 2015 @en
Index UDC 621.3.037.3: 004.04
DOI
Abstract The paper deals with the problem of organization the computations over encrypted data. Recently this problem has become increasingly important due to the extension of the cloud computing paradigm and the need for adequate measures to protect them. However, a number of primitives for working with encrypted data, such as a fully homomorphic encryption, functional encryption, secure multiparty computations and so on solve their problems in a limited context, while building the real secure computing system requires the development of some general theory for organization secure computing, using a systemic approach. We propose to divide all the functionality that the secure computing system must support into the several layers; the interaction between them would be done through the interfaces. Presented six-layer analytical model called "Secure computing interface suite" ("SCIS") is intended to standardize and facilitate the work of researchers and developers in the field of cryptographically secure computing, i.e. such systems in which the untrusted parties processes the sensitive data and therefore the processed information can"t be decrypted at the any stage of processing. For each of the layers we outline the problems researchers deal with, reveal a range of issues that must be addressed, and provide a brief overview of the literature on this topic. The top layer is the most abstract and provides interface for application programmer, followed by two layers dealing with the internal representation of programs, then - a layer designed for analysis and synthesis of the virtual machine architecture, the next layer deals with cryptographic schemes and protocols, and, finally, the layer for hardware implementation of elementary operations. A necessary condition for the working of a cryptographically secure computing system is the development and implementation each of these layers.

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Keywords Fully homomorphic encryption; functional encryption; secure multiparty computations; secure computation system; analytical model; secure cloud computing.
References 1. Guellier A. Can Homomorphic Cryptography ensure Privacy?: diss. Inria; IRISA; Supélec Rennes, équipe Cidre; Université de Rennes 1, 2014.
2. Burtyka P., Makarevich O. Symmetric Fully Homomorphic Encryption Using Decidable Matrix Equations, Proceedings of the 7th International Conference on Security of Information and Networks. ACM, 2014, pp. 186.
3. Burtyka F.B. Simmetrichnoe polnost'yu gomomorfnoe shifrovanie s ispol'zovaniem neprivodimykh matrichnykh polinomov [Symmetric fully homomorphic encryption using irreducible matrix polynomials], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2014, No. 8 (157), pp. 107-122.
4. Burtyka F.B. Paketnoe simmetrichnoe polnost'yu gomomorfnoe shifrovanie na osnove matrichnykh polinomov [Batch fully symmetric homomorphic encryption based on matrix polynomials], Trudy ISP RAN [Proceedings of ISP RAS], 2014, Vol. 26, No. 5, pp. 99-115.
5. Bain A., Mitchell J., Sharma R., Stefan D., Zimmerman J. A domain-specific language for computing on encrypted data, 31st International Conference on Foundations of Software Technology and Theoretical Computer Science, 2011, pp. 6.
6. Malkhi D., Nisan N., Pinkas B., Sella Y. Fairplay – Secure Two-Party Computation System, USENIX Security Symposium, 2004, Vol. 4.
7. Bogetoft P., Christensen, D. L., Damgård, I., Geisler, M., Jakobsen T.P., Krøigaard Nielsen J.D., Nielsen J.B., Nielsen K., Pagter J., Schwartzbach M., and Toft T. Secure multiparty computation goes live, Financial Cryptography and Data Security. Springer Berlin Heidelberg, 2009, pp. 325-343.
8. Nielsen J.D., Schwartzbach M.I. A domain-specific programming language for secure multiparty computation, Proceedings of the 2007 workshop on Programming languages and analysis for security. ACM, 2007, pp. 21-30.
9. Mitchell, J. C., Sharma, R., Stefan, D., Zimmerman, J. Information-flow control for programming on encrypted data, Computer Security Foundations Symposium (CSF), 2012 IEEE 25th. IEEE, 2012, pp. 45-60.
10. Fletcher C. W., Dijk M., Devadas S. Towards an interpreter for efficient encrypted computation, Proceedings of the 2012 ACM Workshop on Cloud computing security workshop. ACM, 2012, pp. 83-94.
11. Zhuravlev D., Samoilovych I., Orlovskyi R., Bondarenko I., Lavrenyuk Y. Encrypted Program Execution, Trust, Security and Privacy in Computing and Communications (TrustCom), 2014 IEEE 13th International Conference on. IEEE, 2014, pp. 817-822.
12. Varnovskiy N. P., Zakharov V.A., Kuzyurin N.N., Shokurov A.V. Sovremennoe sostoyanie issledovaniy v oblasti obfuskatsii programm: opredeleniya stoykosti obfuskatsii [The current state of research in the field of obfuscation programs: determination of resistance obfuscation], Trudy ISP RAN [Proceedings of ISP RAS], 2014, Vol. 26, No. 3. pp. 167-198.
13. Brenner M., Perl H., Smith M. How practical is homomorphically encrypted program execution? An implementation and performance evaluation, Trust, Security and Privacy in Computing and Communications (TrustCom), 2012 IEEE 11th International Conference on. IEEE, 2012, pp. 375-382.
14. Cousins, D. B., Rohloff, K., Peikert, C., Schantz, R. SIPHER: Scalable implementation of primitives for homomorphic encryption–FPGA implementation using Simulink, High Performance Extreme Computing Conference, 2011.
15. Moore C., O'Neill M., Hanley N., O'Sullivan E. Accelerating integer-based fully homomorphic encryption using Comba multiplication, Signal Processing Systems (SiPS), 2014 IEEE Workshop on. IEEE, 2014, pp. 1-6.
16. Doröz Y., Öztürk E., Sunar B. A million-bit multiplier architecture for fully homomorphic encryption, Microprocessors and Microsystems, 2014, Vol. 38, No. 8, pp. 766-775.
17. Wang, W., Hu, Y., Chen, L., Huang, X., & Sunar, B. Accelerating fully homomorphic encryption using GPU, High Performance Extreme Computing (HPEC), 2012 IEEE Conference on. IEEE, 2012, pp. 1-5.
18. Moore C., Hanley N., McAllister J., O’Neill M., O’Sullivan E., Cao X. Targeting FPGA DSP slices for a large integer multiplier for integer based FHE, Financial Cryptography and Data Security. Springer Berlin Heidelberg, 2013, pp. 226-237.
19. Moore C., O'Neill M., O'Sullivan E., Doröz Y., & Sunar B. Practical homomorphic encryption: A survey, Circuits and Systems (ISCAS), 2014 IEEE International Symposium on. IEEE, 2014, pp. 2792-2795.
20. Curatelli F., Mangeruca L. A method for computing the number of iterations in data dependent loops, Real-Time Systems, 2006, Vol. 32, No. 1-2, pp. 73-104.

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