Advertisement

A Multi-dimensional Adversary Analysis of RSA and ECC in Blockchain Encryption

  • Sonali ChandelEmail author
  • Wenxuan Cao
  • Zijing Sun
  • Jiayi Yang
  • Bailu Zhang
  • Tian-Yi Ni
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 70)

Abstract

During this current age of big data, the security of sensitive data in the cyberspace has become utmost important. Blockchain, as a new age technology, provides the necessary tools to ensure data integrity and data protection using some encryption. Smaller transaction size and higher transaction efficiency are the essential requirements of the blockchain. However, these requirements are closely related to the efficiency of the encryption algorithms that blockchain uses. In this paper, we have analyzed and compared the performance of Rivest-Shamir-Adleman (RSA) algorithm and Elliptic Curve Cryptography (ECC) algorithm that is most commonly used in blockchain by having a general consideration of a transaction size and transaction efficiency. We aim to provide a better understanding of the reason behind their extensive use in the blockchain. We hope that our evaluation and analysis of these two encryption algorithms can help promote the further development of blockchain.

Keywords

Blockchain Encryption algorithms ECC RSA Privacy 

References

  1. 1.
    Schwab, K., Marcus, A., Oyola, JO., Hoffman, W., Luzi, M.: Personal data: the emergence of a new asset class. In an Initiative of the World Economic Forum (2011)Google Scholar
  2. 2.
    National security agency: The Case For Elliptic Curve Cryptography, (nsa.gov). http://www.nsa.gov/business/programs/elliptic_curve.html (2009). Last accessed 15 Jan 2009
  3. 3.
    Jansma, N., Arrendondo, B.: Performance Comparison of Elliptic Curve and RSA Digital Signatures. (2004). Accessed on 28 Apr 2004Google Scholar
  4. 4.
    Lee Kuo Chuen, D. (ed.) Handbook of digital currency, 1st edn, Elsevier (2015)Google Scholar
  5. 5.
    Zheng, Z., Xie, S., Dai, H., Chen, X., Wang, H.: An overview of blockchain technology: architecture, consensus, and future trends. In: 2017 IEEE 6th International Congress on Big Data, June 2017Google Scholar
  6. 6.
  7. 7.
    Kumar, A., Tyagi, S.S., Rana, M., Aggarwal, N., Bhadana, P.: A comparative study of public key cryptosystem based on ECC and RSA, (May 2011)Google Scholar
  8. 8.
  9. 9.
    Symmetric vs Asymmetric Encryption—What are the differences? https://www.ssl2buy.com/wiki/symmetric-vs-asymmetric-encryption-what-are-differences
  10. 10.
  11. 11.
    Savari, M., Montazerolzohour, M., Thiam, Y.E.: Comparison of ECC and RSA algorithm in multipurpose smart card applicationGoogle Scholar
  12. 12.
    da Silva Quirin, G., Moreno, ED.: Architectural evaluation of algorithms RSA, ECC and MQQ in arm processors. Int. J. Comput. Net. Commun. (IJCNC). 5(2), (2013)Google Scholar
  13. 13.
    Ting-ting, G., Tao, L.: The implementation of RSA public-key algorithm and RSA signature algorithm. Department of Computer Science, Sichuan University (1999)Google Scholar
  14. 14.
    Han, M., Zhang, R., Qiu, T., Xu, M., Ren, W.: Multivariate, chaotic time series prediction based on improved grey relational analysis, Senior Member, IEEE (2017)Google Scholar
  15. 15.
    Michael Hamburg “Which one is better: elliptic curve cryptography or RSA algorithm and why?” https://www.quora.com/Which-one-is-better-elliptic-curve-cryptography-or-RSA-algorithm-and-why
  16. 16.
    Bafandehkar, M., Yasin, SM., Mahmod, R., Hanapi, Z.M.: Comparison of ECC and RSA algorithm in resource-constrained devices. In: International Conference on It Convergence & Security, 3 Jan 2013Google Scholar
  17. 17.
    Dong, D., Yan, Y., Wang, Z.: Application of grey correlative model for surface quality evaluation of strip steel based on the variation coefficient method. In: 2011 International Conference on Electronic & Mechanical Engineering and Information TechnologyGoogle Scholar
  18. 18.
    Primasari, C.H., Setyohadi, D.B.: Financial analysis and TOPSIS implementation for selecting the most profitable investment proposal in goat farming. In: 2017 2nd International Conferences on Information Technology, Information Systems and Electrical Engineering (ICITISEE) (2017)Google Scholar
  19. 19.
    García-Cascales, M.S., Lamata, M.T.: On rank reversal and TOPSIS method. Math. Comput. Model. 56(5), 123–132 (2012)MathSciNetCrossRefGoogle Scholar
  20. 20.
    Zhou, L., Wang, Y., Wang, F., Yan, C., Bi, J.: A transformer fault diagnosis method based on grey relational analysis and integrated weight determination, IEEE, (June 2017)Google Scholar
  21. 21.
    Khurana, A., Sharma, T., Shukla, K.K.: Optimization of parameters affecting the performance of wind turbine blade using grey relational analysis, IEEE (2017)Google Scholar
  22. 22.
    Lenstra, Arjen K, Key Lengths: Contribution to The Handbook of Information Security, Citibank, N.A., and Technische Universiteit Eindhoven, 1 North Gate Road, Mendham, NJ 07945–3104, U.S.AGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Sonali Chandel
    • 1
    Email author
  • Wenxuan Cao
    • 1
  • Zijing Sun
    • 1
  • Jiayi Yang
    • 1
  • Bailu Zhang
    • 1
  • Tian-Yi Ni
    • 2
  1. 1.New York Institute of TechnologyNanjingChina
  2. 2.Arizona State UniversityTempeUSA

Personalised recommendations