HD-Sign: Hardware Based Digital Signature Generation Using True Random Number Generator

  • Authors

    • Anahita G
    • Krishnapriya KPM
    • Shiva Prasad R
    • Mohan Kumar N
    2018-07-07
    https://doi.org/10.14419/ijet.v7i3.8.16850
  • Hardware Security, Digital Signature, Random number, TRNG, Public key cryptography, NIST

  • Abstract

    With the recent advancements in the field of computing, a fair share of easier and safer practices to exchange and share information between multiple parties have propped up. While some of these are improvisations, a few such as the Digital Signatures, have fast replaced conventional signing practices. It’s wide use and acceptance in the industry as well as officially, has necessitated higher security to protect data integrity and privacy. These digital Signatures are generated on the basis of various schemes that are designed to accommodate efficiency, crypto security and algorithmic complexity. This paper proposes an alternate method named HD-SIGN for generating these digital signatures in accordance with Secure Hash Function and 512-bit SRNN cryptographic algorithm. With the aid of a TRNG module, a modification to produce a large number with two prime factors and a set of natural numbers in a pair of public and private keys has been incorporated. The LSFR based TRNG module which helps maintain the ‘True Randomness’ of any generated number has been used for this purpose. Further, the random nature of the generated sequence to be used in the digital signature, has been tested with the help of standard NIST tests. The Hamming distance has also been analyzed as a security metric for the proposal, implying the degree of unpredictability of the generated true random sequences.

     

     

  • References

    1. [1] Negi, D., Negi, A. and Agarwal, S., 2016. The complex key cryptosystem. Int. J. Appl. Eng. Res, 11, pp.681-684.

      [2] Verma, Amit, Simarpreet Kaur, and Bharti Chhabra. "Design and Development of Robust Algorithm for Cryptography using improved AES technique "; International Journal of Computer Science and Information Security 15.3 (2017): 66.

      [3] Faz-Hernández, Armando, et al. "A Secure and Efficient Implementation of the Quotient Digital Signature Algorithm (qDSA)." International Conference on Security, Privacy, and Applied Cryptography Engineering. Springer, Cham, 2017.

      [4] McKay, Kerry A., Kerry A. McKay, Larry Bassham, Meltem Sonmez Turan, and Nicky Mouha. Report on lightweight cryptography. US Department of Commerce, National Institute of Standards and Technology, 2017.

      [5] Polk, W. Timothy, et al. "Cryptographic algorithms and key sizes for personal identity verification." NIST Special Publication 800 (2015): 78-4.

      [6] Bansal, Dimple, Manish Sharma, and Aayushi Mishra. "Analysis of Digital Signature based Algorithm for Authentication and Privacy in Digital Data." International Journal of Computer Applications 161.5 (2017).

      [7] Chen FL, Liu WF, Chen SG, Wang ZH. Public-key quantum digital signature scheme with one-time pad private-key. Quantum Information Processing. 2018 Jan 1;17(1):10.

      [8] Buchovecká S, Lórencz R, Kodýtek F, Bucek J. True random number generator based on ROPUF circuit. InDigital System Design (DSD), 2016 Euromicro Conference on 2016 Aug 31 (pp. 519-523). IEEE.

      [9] Xiao-fei, L., Xuan-jing, S., & Hai-peng, C. (2010, April). An improved ElGamal digital signature algorithm based on adding a random number. In Networks Security Wireless Communications and Trusted Computing (NSWCTC), 2010 Second International Conference on (Vol. 2, pp. 236-240). IEEE.

      [10] Dworkin, Morris J. SHA-3 standard: Permutation-based hash and extendable-output functions. No. Federal Inf. Process. Stds.(NIST FIPS)-202. 2015.

      [11] Zhu, Chengzhang, Longbing Cao, Qiang Liu, Jianping Yin, and Vipin Kumar. "Heterogeneous metric learning of categorical data with hierarchical couplings." IEEE Transactions on Knowledge and Data Engineering (2018).

      [12] Varchola, Michal. "FPGA based true random number generators for embedded cryptographic applications." Dec 1 (2008): 74-76.

      [13] Shiva Prasad R., Anirudh Siripagada, Santthosh Selvaraj, Mohankumar N. "Random Seeding LFSR based TRNG for Hardware Security Applications", Proc. of 2nd Intl. Conf. on Integrated Intelligent Computing, Communication & Security (ICIIC-2018), 2018

      [14] Manoj Reddy, Akshay K P, Giridhar R, Kharan SD, Mohankumar N, "BHARKS: Built-in hardware authentication using random key sequence, Proc of 4th IEEE Conference on Signal Processing Computing and Control (ISPCC), pp 200-204, Salon, 2017

      [15] Tang, Q., Kim, B., Lao, Y., Parhi, K. K., & Kim, C. H. (2014, September). True random number generator circuits based on single-and multi-phase beat frequency detection. In Custom Integrated Circuits Conference (CICC), 2014 IEEE Proceedings of the (pp. 1-4). IEEE.

      [16] Ashok Kumar Mohan; Dr. Nirmala Devi M.; Dr. M. Sethumadhavan; Santhya R.,"A Selective Generation of Hybrid Random Numbers via Android Smart Phones", International Journal of Pure and Applied Mathematics, Volume 118 (2018)

  • Downloads

  • How to Cite

    G, A., KPM, K., Prasad R, S., & Kumar N, M. (2018). HD-Sign: Hardware Based Digital Signature Generation Using True Random Number Generator. International Journal of Engineering & Technology, 7(3.8), 147-150. https://doi.org/10.14419/ijet.v7i3.8.16850

    Received date: 2018-08-05

    Accepted date: 2018-08-05

    Published date: 2018-07-07