Preview

Scientific and Technical Journal of Information Technologies, Mechanics and Optics

Advanced search

An optimal swift key generation and distribution for QKD

https://doi.org/10.17586/2226-1494-2022-22-1-101-113

Abstract

Secured transmission between users is essential for communication system models. Recently, cryptographic schemes were introduced for secured transmission and secret transmission between cloud users. In a cloud environment, there are many security issues that occur among the cloud users such as, account hacking, data breaches, broken authentication, compromised credentials, and so on. Quantum mechanics has been implemented in cryptography that made it efficient for strong security concerns over outsourced data in a cloud environment. Therefore, the present research focuses on providing excellent security for cloud users utilizing a swift key generation model for QKD cryptography. The Quantum Key Distribution (QKD) is an entirely secure scheme known as Cloud QKDP. Initially, a random bit sequence is generated to synchronize the channel. An eavesdropper will not permit to synchronize parameters between them. In this key reconciliation technique, the random bit sequence is concatenated with the photon polarisation state. BB84 protocol is improved by optimizing its bit size using FireFly Optimization (FFO) at the compatibility state, and in the next state, both transmitter and receiver generate a raw key. Once the key is generated, it is then used for the transmission of messages between cloud users. Furthermore, a Python environment is utilized to execute the proposed architecture, and the accuracy rate of the proposed model attained 98 %, and the error rate is 2 %. This proves the performance of the proposed firefly optimization algorithm based swift key generation model for QKD performs better than previous algorithms.

About the Authors

M. R. Suma
Dayananda Sagar College of Engineering
India

Mallavalli Raghavendra Suma — Assistant Professor

Bengaluru, 560078



P. Madhumathy
RV Institute of Technology and Management
India

Perumal Madhumathy — PhD, Associate Professor

Bengaluru, 560076



References

1. Kiktenko E.O., Malyshev A.O., Gavreev M.A., Bozhedarov A.A., Pozhar N.O., Anufriev M.N., Fedorov A.K. Lightweight authentication for quantum key distribution // IEEE Transactions on Information Theory. 2020. V. 66. N 10. P. 6354–6368. https://doi.org/10.1109/TIT.2020.2989459

2. Chitambar E., Fortescue B., Hsieh M.H. The conditional common information in classical and quantum secret key distillation // IEEE Transactions on Information Theory. 2018. V. 64. N 11. P. 7381–7394. https://doi.org/10.1109/TIT.2018.2851564

3. Ji Z., Yeoh P.L., Zhang D., Chen G., Zhang Y., He Z., Yin H. Secret key generation for intelligent reflecting surface assisted wireless communication networks // IEEE Transactions on Vehicular Technology. 2021. V. 70. N 1. P. 1030–1034. https://doi.org/10.1109/TVT.2020.3045728

4. Zhang W.R. From equilibrium-based business intelligence to information conservational quantum-fuzzy cryptography – a cellular transformation of bipolar fuzzy sets to quantum intelligence machinery // IEEE Transactions on Fuzzy Systems. 2018. V. 26. N 2. P. 656–669. https://doi.org/10.1109/TFUZZ.2017.2687408

5. Koziel B., Azarderakhsh R., Kermani M.M., Jao D. Post-quantum cryptography on FPGA based on isogenies on elliptic curves // IEEE Transactions on Circuits and Systems I: Regular Papers. 2017. V. 64. N 1. P. 86–99. https://doi.org/10.1109/TCSI.2016.2611561

6. Yang Y.G., Xu P., Yang R., Zhou Y.H., Shi W.M. Quantum Hash function and its application to privacy amplification in quantum key distribution, pseudo-random number generation and image encryption // Scientific Reports. 2016. V. 6. N 1. P. 19788. https://doi.org/10.1038/srep19788

7. Chen Z., Zhou K., Liao Q. Quantum identity authentication scheme of vehicular ad-hoc networks // International Journal of Theoretical Physics. 2019. V. 58. N 1. P. 40–57. https://doi.org/10.1007/s10773-018-3908-y

8. Xu F., Curty M., Qi B., Lo H.K. Measurement-device-independent quantum cryptography // IEEE Journal of Selected Topics in Quantum Electronics. 2015. V. 21. N 3. P. 148–158. https://doi.org/10.1109/JSTQE.2014.2381460

9. Dong T., Huang T. Neural cryptography based on complex-valued neural network // IEEE Transactions on Neural Networks and Learning Systems. 2020. V. 31. N 11. P. 4999–5004. https://doi.org/10.1109/TNNLS.2019.2955165

10. Bai Z., Yang S., Li Y. High-efficiency reconciliation for continuous variable quantum key distribution // Japanese Journal of Applied Physics. 2017. V. 56. N 4. P. 044401. https://doi.org/10.7567/JJAP.56.044401

11. Shang T., Chen R., Lei Q. Quantum random oracle model for quantum public-key encryption // IEEE Access. 2019. V. 7. P. 130024–130031. https://doi.org/10.1109/ACCESS.2019.2940406

12. Zoni D., Galimberti A., Fornaciari W. Efficient and scalable FPGAoriented design of QC-LDPC bit-flipping decoders for post-quantum cryptography // IEEE Access. 2020. V. 8. P. 163419–163433. https://doi.org/10.1109/ACCESS.2020.3020262

13. Broadbent A., Schaffner C. Quantum cryptography beyond quantum key distribution // Designs, Codes, and Cryptography. 2016. V. 78. N 1. P. 351–382. https://doi.org/10.1007/s10623-015-0157-4

14. Shenoy-Hejamadi A., Pathak A., Radhakrishna S. Quantum cryptography: key distribution and beyond // Quanta. 2017. V. 6. N 1. P. 1–47. https://doi.org/10.12743/quanta.v6i1.57

15. Chan A.C. Distributed private key generation for identity based cryptosystems in ad hoc networks // IEEE Wireless Communications Letters. 2012. V. 1. N 1. P. 46–48. https://doi.org/10.1109/WCL.2012.120211.110130

16. Jin R., Du X., Zeng K., Huang L., Xiao L., Xu J. Delay analysis of physical-layer key generation in dynamic roadside-to-vehicle networks // IEEE Transactions on Vehicular Technology. 2017. V. 66. N 3. P. 2526–2535. https://doi.org/10.1109/TVT.2016.2582853

17. Wang J., Cheng L.M., Su T. Multivariate cryptography based on clipped hopfield neural network // IEEE Transactions on Neural Networks and Learning Systems. 2018. V. 29. N 2. P. 353–363. https://doi.org/10.1109/TNNLS.2016.2626466

18. Xu P., Cumanan K., Ding Z., Dai X., Leung K.K. Group secret key generation in wireless networks: algorithms and rate optimization // IEEE Transactions on Information Forensics and Security. 2016. V. 11. N 8. P. 1831–1846. https://doi.org/10.1109/TIFS.2016.2553643

19. Howe J., Khalid A., Rafferty C., Regazzoni F., O’Neill M. On practical discrete Gaussian samplers for lattice-based cryptography // IEEE Transactions on Computers. 2018. V. 67. N 3. P. 322–334. https://doi.org/10.1109/TC.2016.2642962

20. Dey S., Hossain A. Session-key establishment and authentication in a smart home network using public key cryptography // IEEE Sensors Letters. 2019. V. 3. N 4. P. 8667393. https://doi.org/10.1109/LSENS.2019.2905020

21. Zhang J., He B., Duong T.Q. Woods R. On the key generation from correlated wireless channels // IEEE Communications Letters. 2017. V. 2 1 . N 4 . P. 9 6 1 – 9 6 4 . https://doi.org/10.1109/LCOMM.2017.2649496

22. He D., Zeadally S. An analysis of RFID authentication schemes for internet of things in healthcare environment using elliptic curve cryptography // IEEE Internet of Things Journal. 2015. V. 2. N 1. P. 72–83. https://doi.org/10.1109/JIOT.2014.2360121

23. Furqan H.M., Hamamreh J.M., Arslan H. New Physical layer key generation dimensions: Subcarrier indices/positions-based key generation // IEEE Communications Letters. 2021. V. 25. N 1. P. 59– 63. https://doi.org/10.1109/LCOMM.2020.3025262

24. Almajed H.N., Almogren A.S. SE-ENC: A secure and efficient encoding scheme using elliptic curve cryptography // IEEE Access. 2019. V. 7. P. 175865–175878. https://doi.org/10.1109/ACCESS.2019.2957943


Review

For citations:


Suma M.R., Madhumathy P. An optimal swift key generation and distribution for QKD. Scientific and Technical Journal of Information Technologies, Mechanics and Optics. 2022;22(1):101-113. https://doi.org/10.17586/2226-1494-2022-22-1-101-113

Views: 10


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2226-1494 (Print)
ISSN 2500-0373 (Online)