ISSN No:2250-3676 ----- Crossref DOI Prefix: 10.64771 ----- Impact Factor: 9.625
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    EXPLORING QUANTUM CRYPTOGRAPHY VS TRADITIONAL CRYPTOGRAPHY IN SECURING IOT DEVICES

    R. Pradeep Kumar Reddy, G. Madhavi

    Author

    ID: 3047

    DOI: Https://doi.org/10.64771/ijesat.2023.v23.i10.3047

    Abstract :

    The Rapid Growth Of IoT (Internet Of Things) Devices Has Led To An Increased Focus On Securing These Networks, As They Handle Vast Amounts Of Sensitive Data. Traditional Cryptographic Algorithms Such As RSA, AES, And ECC Have Been Widely Used To Secure IoT Devices, But The Advent Of Quantum Computing Poses Significant Threats To These Methods. This Paper Provides A Comparative Analysis Of Traditional Cryptography And Quantum-safe Algorithms, Including Lattice-based Cryptography, Multivariate Cryptography, And Quantum Key Distribution (QKD), In The Context Of IoT Security. Key Performance Metrics Such As Encryption And Decryption Time, Energy Consumption, Scalability, And Resistance To Quantum Attacks Are Evaluated. The Results Indicate That While Traditional Cryptographic Methods Are Efficient And Scalable For Current IoT Networks, They Are Vulnerable To Future Quantum Attacks. On The Other Hand, Quantum-safe Algorithms, Though More Computationally Intensive, Offer Enhanced Security But Present Challenges In Scalability And Energy Efficiency. This Study Highlights The Need For Further Optimization Of Quantum Cryptographic Methods To Ensure The Secure And Efficient Operation Of IoT Devices In The Quantum Era.

    Published:

    11-10-2023

    Issue:

    Vol. 23 No. 10 (2023)


    Page Nos:

    120-132


    Section:

    Articles

    License:

    This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

    How to Cite

    R. Pradeep Kumar Reddy, G. Madhavi, EXPLORING QUANTUM CRYPTOGRAPHY VS TRADITIONAL CRYPTOGRAPHY IN SECURING IOT DEVICES , 2023, International Journal of Engineering Sciences and Advanced Technology, 23(10), Page 120-132, ISSN No: 2250-3676.

    DOI: https://doi.org/10.64771/ijesat.2023.v23.i10.3047