Abstract
The preservation of privacy has become a widely discussed topic on the Internet. Encryption is an approach to privacy; however, to outsource computing to an cloud service without revealing private information over encrypted data is difficult. Homomorphic encryption can contribute to it but is based on complicated mathematical structures of abstract algebra. We propoase a new scheme for securely computing the similarity between binary vectors through a cloud server. The scheme is constructed from ciphertext policy attribute based encryption and garbled circuits rather than homomorphic encryption. Attribute based encryption provides the access power, which is a necessary primitive in our scheme. Moreover, for computing over encrypted data, we rely on garbled circuits to handle secure outsourcing and to avoid the use of homomorphic encryption.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Benaloh, J., Chase, M., Horvitz, E., et al.: Patient controlled encryption: ensuring privacy of electronic medical records, pp. 103–114 (2009)
Ryu, E.K., Takagi, T.: Efficient conjunctive keyword-searchable encryption. In: International Conference on Advanced Information Networking and Applications Workshops, pp. 409–414. IEEE (2007)
Chen, Z., Wu, C., Wang, D., et al.: Conjunctive keywords searchable encryption with efficient pairing, constant ciphertext and short trapdoor. In: Intelligence and Security Informatics, pp. 176–189. Springer, Heidelberg (2012)
Zhang, L.: Privacy-preserving computing and applications. Ph.D. thesis, Tsinghua University (2014)
Zhang, L., Jung, T., Liu, C., et al.: POP: privacy-preserving outsourced photo sharing and searching for mobile devices. In: IEEE International Conference on Distributed Computing Systems, pp. 308–317. IEEE (2015)
Bethencourt, J., Sahai, A., Waters, B.: Ciphertext-policy attribute-based encryption. In: IEEE Symposium on Security and Privacy, pp. 321–334. IEEE Computer Society (2007)
Lai, J., Deng, R.H., Li, Y.: Fully secure cipertext-policy hiding CP-ABE. In: International Conference on Information Security Practice and Experience, pp. 24–39. Springer-Verlag (2011)
Kumar, S.N.: Cryptography during data sharing and accessing over cloud. Int. Trans. Electr. Comput. Eng. Syst. 3(1), 12–18 (2015)
Paillier, P.: Public-key cryptosystems based on composite degree residuosity classes. In: International Conference on Theory and Application of Cryptographic Techniques, pp. 223–238. Springer-Verlag (1999)
Garg, S., Lu, S., Ostrovsky, R., et al.: Garbled RAM from one-way functions. In: STOC (2015)
Yao, C.C.: How to generate and exchange secrets. In: Symposium on Foundations of Computer Science, 1986, pp. 162–167. IEEE (1986)
Gentry, C., Halevi, S., Lu, S., et al.: Garbled RAM revisited. In: International Workshop/Conference on Theory and Application of Cryptographic Techniques, pp. 405–422. Springer, Heidelberg (2014)
Huang, Y., Evans, D., Katz, J., et al.: Faster secure two-party computation using garbled circuits. In: Usenix Conference on Security, p. 35. USENIX Association (2011)
Acknowledgements
This work was partially supported by the Innovation Center for Big Data and Digital Convergence, Yuan Ze University, and the Ministry of Science and Technology of Taiwan under grant no. 106-2218-E-155-008-MY3. We also acknowledge Wallace Academic Editing for editing this manuscript.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Yang, D., Chen, YC., Ye, S. (2018). Privacy-Preserving Outsource Computing for Binary Vector Similarity. In: Peng, SL., Wang, SJ., Balas, V., Zhao, M. (eds) Security with Intelligent Computing and Big-data Services. SICBS 2017. Advances in Intelligent Systems and Computing, vol 733. Springer, Cham. https://doi.org/10.1007/978-3-319-76451-1_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-76451-1_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-76450-4
Online ISBN: 978-3-319-76451-1
eBook Packages: EngineeringEngineering (R0)