Abstract
Privacy-preserving big data analysis on cloud systems is becoming increasingly indispensable as the amount of information of the individuals is accumulated on our database system. As a way of maintaining security on cloud system, Homomorphic Encryption (HE) is considered to be theoretically eminent protecting against privacy leakage. However, insufficient number of operations on HE are developed, hindering many research developers to apply their knowledgeable techniques on this field. Therefore, we propose a novel approach in constructing logarithm function based on mathematical theorem of Taylor expansion with fundamental arithmetic operations and basic gate operations in usage. Moreover, we present a more accurate way of deriving answers for logarithm using square and shift method.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Jain, P., Gyanchandani, M., Khare, N.: Differential privacy: its technological prescriptive using big data. J. Big Data 5(1), 15 (2018)
Dwork, C., Roth, A., et al.: The algorithmic foundations of differential privacy. Found. Trends® Theor. Comput. Sci. 9(3–4), 211–407 (2014)
Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Faster fully homomorphic encryption: bootstrapping in less than 0.1 seconds. In: Cheon, J.H., Takagi, T. (eds.) ASIACRYPT 2016. LNCS, vol. 10031, pp. 3–33. Springer, Heidelberg (2016). https://doi.org/10.1007/978-3-662-53887-6_1
Chillotti, I., Gama, N., Georgieva, M., Izabachène, M.: Improving TFHE: faster packed homomorphic operations and efficient circuit bootstrapping. Cryptology ePrint Archive, Report 2017/430 (2017)
Turner, C.: A fast binary logarithm algorithm. In: Streamlining Digital Signal Processing: A Tricks of the Trade Guidebook, pp. 281–283, Wiley, Hoboken (2012)
Rivest, R., Adleman, L., Dertouzos, M.: On data banks and privacy homomorphisms. Found. Secure Comput. 4(11), 169–180 (1978)
Gentry, C.: Fully homomorphic encryption using ideal lattices. In: STOC, vol. 9 (2009)
Zaki, M.J., Meira, W., Meira, W.: Data Mining and Analysis: Fundamental Concepts and Algorithms. Cambridge University Press, Cambridge (2014)
Nasrabadi, N.: Pattern recognition and machine learning. J. Electron. Imaging 16, 049901 (2007)
Hogg, R., McKean, J., Craig, A.: Introduction to Mathematical Statistics, 2nd edn. Pearson Education, London (2005)
Acknowledgement
This research was supported by the MSIP (Ministry of Science, ICT & Future Planning), Korea, under the IITP (Institute for Information & communications Technology Promotion) support program (2017-0-00545).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Yoo, J.S., Song, B.K., Yoon, J.W. (2019). Logarithm Design on Encrypted Data with Bitwise Operation. In: Kang, B., Jang, J. (eds) Information Security Applications. WISA 2018. Lecture Notes in Computer Science(), vol 11402. Springer, Cham. https://doi.org/10.1007/978-3-030-17982-3_9
Download citation
DOI: https://doi.org/10.1007/978-3-030-17982-3_9
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-17981-6
Online ISBN: 978-3-030-17982-3
eBook Packages: Computer ScienceComputer Science (R0)