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CryptoHHO: a bio-inspired cryptosystem for data security in Fog–Cloud architecture

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Abstract

The exponential growth of Internet-of-Things (IoT) has raised several data security risks to the Fog–Cloud architecture. The performance and the computation cost of security algorithms hinder providing a secure real-time environment for IoT. This study proposes a novel two-layer cryptosystem, Cryptographic Harris Hawks Optimization (CryptoHHO), for Fog–Cloud architecture that reduces security overheads while maintaining confidentiality, integrity, and availability. The first layer of the proposed CryptoHHO is responsible for generating a highly randomized key using HHO to optimize Shannon entropy incorporation with transfer functions and a binarization mechanism. The second layer of CryptoHHO introduces a novel encipher model for encryption and decryption based on the Shift cipher, XOR operator, and an instance of crossover and mutation. The job execution avenue, i.e., Fog or cloud computing, is selected depending on the size of IoT requests, security sensitivity, and time sensitivity. The performance of CryptoHHO is compared against other emerging bio-inspired cryptographic algorithms. It was found that the CryptoHHO performs better than CryptoSSA, CryptoGWO, CryptoPSO, and CryptoWOA algorithms based on entropy, key generation time, transfer function comparison, execution time, and throughput. Further, the robustness of CryptoHHO is examined by various security analyses like brute-force attack resistivity, confusion-diffusion, CIA achievement, and statistical evaluations suggested by NIST and FIPS.

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  1. Department of Computer Science, Aligarh Muslim University, Aligarh, India

    Md Saquib Jawed & Mohammad Sajid

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MS and MSJ were contributed to conceptualization; MSJ was contributed to methodology, formal analyses, data curation, and original draft preparation; MS was contributed to writing—review and editing, supervision.

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Correspondence to Md Saquib Jawed.

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Jawed, M.S., Sajid, M. CryptoHHO: a bio-inspired cryptosystem for data security in Fog–Cloud architecture. J Supercomput (2024). https://doi.org/10.1007/s11227-024-06055-3

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