Abstract
Cloud computing has created an intense impact over different applications with limited computational resources. Since, it works on pay-per-use manner; a massive amount of computational power is utilized. Anyhow, Security is the most vital thing for the outsourced data in cloud systems. Thus, secure outsourcing mechanisms are in great need to not only protect sensitive information by enabling computations with encrypted data, but also protect customers from malicious behaviors by validating the computation result. Such a mechanism of general secure computation outsourcing was recently shown to be feasible in theory, but to design mechanisms that are practically efficient remains a very challenging problem. In this paper, we focus on providing security to the outsourced data via improved Lattice-Based Encryption (LBE). Identifying hard computational problems which are amenable for cryptographic use is a very important task. With the help of Linear Programming (LP) solver, the cloud data are encrypted using LBE model which provides strong security proofs for the outsourced data. Initially, we will discover the highly significant sensitive attributes and stored in the lattice structure. LP solver is used as the cost objective function that minimizes the computational cost for every larger computational data used for outsourcing to the cloud server. Time is the research metric used for validating the proposed model via effectiveness, efficiency and outsourcing key generation. It is evident from the analysis that our proposed data outsourcing model ensures lessened overhead with lessened time taken for computing larger number of users.
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References
Wang, C., et al.: Secure and practical outsourcing of linear programming in cloud computing. In: IEEE INFOCOM (2011)
Cloud Security Alliance: Security guidance for critical areas of focus in cloud computing. (2009). http://www.cloudsecurityalliance.org
Gentry, C.: Computing arbitrary functions of encrypted data. Commun. ACM 53(3), 97–105 (2010)
Sun Microsystems, Inc.: Building customer trust in cloud computing with transparent security (2009). https://www.sun.com/offers/details/suntransparency.xml
Atallah, M.J., Pantazopoulos, K.N., Rice, J.R., Spafford, E.H.: Secure outsourcing of scientific computations. Adv. Comput. 54, 216–272 (2001)
Hohenberger, S., Lysyanskaya, A.: How to securely outsource cryptographic computations. In: Proceedings of the TCC, pp. 264–282 (2005)
Atallah, M.J., Li, J.: Secure outsourcing of sequence comparisons. Int. J. Inf. Sec. 4(4), 277–287 (2005)
Benjamin, D., Atallah, M.J.: Private and cheating-free outsourcing of algebraic computations. In: Proceedings of the 6th Conference on Privacy, Security, and Trust (PST), pp. 240–245 (2008)
Gennaro, R., Gentry, C., Parno, B.: Non-interactive verifiable computing: outsourcing computation to untrusted workers. In: Proceedings of the CRYPTO’10, Aug. 2010
Atallah, M., Frikken, K.: Securely outsourcing linear algebra computations. In: Proceedings of the ASIACCS, pp. 48–59 (2010)
Yao, A.C.-C.: Protocols for secure computations (extended abstract). In: Proceedings of the FOCS’82, pp. 160–164 (1982)
Gentry, C.: Fully homomorphic encryption using ideal lattices. In: Proceeding of the STOC, pp. 169–178 (2009)
Luenberger, D., Ye, Y.: Linear and Nonlinear Programming, 3rd edn. Springer (2008)
Liu, X., Deng, R.H., Ding, W., Lu, R., Qin, B.: Privacy-preserving outsourced calculation on floating point numbers. IEEE Trans. Inf. Forensics Secur. 11(11), 2513–2527 (2016)
Even, S., Goldreich, O., Lempel, A.: A randomized protocol for signing contracts. Commun. ACM 28(6), 637–647 (1985)
Liu, X., Deng, R.H., Choo, K.-K.R., Weng, J.: An efficient privacypreserving outsourced calculation toolkit with multiple keys. IEEE Trans. Inf. Forensics Secur. 11(11), 2401–2414 (2016)
Blanton, M., Atallah, M.J., Frikken, K.B., Malluhi, Q.: Secure and efficient outsourcing of sequence comparisons. In: Computer Security, pp. 505–522. Springer (2012)
Yu, J., Ren, K., Wang, C.: Enabling cloud storage auditing with verifiable outsourcing of key updates. IEEE Trans. Inf. Forensics Secur. 11(6), 1362–1375 (2016)
Hu, S., Wang, Q., Wang, J., Qin, Z., Ren, K.: Securing SIFT: Privacy-preserving outsourcing computation of feature extractions over encrypted image data. IEEE Trans. Image Process. 25(7), 3411–3425 (2016)
Goldwasser, S., Kalai, Y.T., Rothblum, G.N.: Delegating computation: interactive proofs for muggles. In: Proceedings of the STOC, pp. 113–122 (2008)
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Rao, V.S., Satyanarayana, N. (2019). Improved Lattice-Based Encryption with LP Solver for Secured Outsourced Data in Cloud Computing. In: Abraham, A., Dutta, P., Mandal, J., Bhattacharya, A., Dutta, S. (eds) Emerging Technologies in Data Mining and Information Security. Advances in Intelligent Systems and Computing, vol 755. Springer, Singapore. https://doi.org/10.1007/978-981-13-1951-8_27
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DOI: https://doi.org/10.1007/978-981-13-1951-8_27
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