Optimized data security and storage using improved blowfish and modular encryption in cloud-based internet of things

Saritha Ibakkanavar Guddappa, Sowmyashree Malligehalli Shivakumaraswamy, Naveen Ibakkanavar Guddappa

Abstract


The increasing development of the internet of things (IoT) has made cloud-based storage systems essential for storing, processing, and sharing IoT data. Ensuring cloud security is crucial as it manages a large volume of sensitive and outsourced data vulnerable to unauthorized access. This research proposes an improved blowfish algorithm and modular encryption standard (IBA-MES) for secure and efficient data storage in cloud-based IoT systems. The block cipher structure in IBA enables scaling for different data sizes, ensuring secure data handling across a wide range of IoT devices. Additionally, IBA-MES adaptability helps maintain data integrity, enhancing both the security and efficiency of data storage in cloud-based IoT environments. Modular encryption standard (MES) reduces latency during encryption operations, ensuring quick data transactions between the cloud server and IoT devices. By combining blowfish’s speed and strength with modular encryption’s adaptability, IBA-MES provides robust data protection. Metrics such as execution time, central processing unit (CPU) usage, encryption time, decryption time, runtime, and latency are calculated for the proposed IBA-MES. For 700 blocks, the IBA-MES achieves encryption and decryption times of 270 and 415 ms, respectively, outperforming the triple data encryption standard (TDES).

Keywords


Cloud-based storage system; Efficient data storage; Improved blowfish algorithm; Internet of things; Modular encryption standard

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DOI: http://doi.org/10.11591/ijai.v14.i4.pp2667-2675

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IAES International Journal of Artificial Intelligence (IJ-AI)
ISSN/e-ISSN 2089-4872/2252-8938 
This journal is published by the Institute of Advanced Engineering and Science (IAES).

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