Hemant Kumar

Work place: Department of Computer Science, Babasaheb Bhimrao Ambedkar University, Lucknow, India

E-mail: hemant20192@gmail.com

Website:

Research Interests: Machine Learning, Cyber Security, Engineering

Biography

Hemant Kumar received MCA degree from Subharti University in 2018 and presently pursuing Ph.D. programme in Computer Science from Babasaheb Bhimrao Ambedkar University, Lucknow. He has published several research articles in the field of Software Testing and Machine Learning. His research interests are Software Engineering, Artificial Intelligence, Machine Learning and Cyber Security.

Author Articles
Secure Data Storage and Retrieval over the Encrypted Cloud Computing

By Jaydip Kumar Hemant Kumar Karam Veer Singh Vipin Saxena

DOI: https://doi.org/10.5815/ijcnis.2024.04.04, Pub. Date: 8 Aug. 2024

Information security in cloud computing refers to the protection of data items such as text, images, audios and video files. In the modern era, data size is increasing rapidly from gigabytes to terabytes or even petabytes, due to development of a significant amount of real-time data. The majority of data is stored in cloud computing environments and is sent or received over the internet. Due to the fact that cloud computing offers internet-based services, there are various attackers and illegal users over the internet who are consistently trying to gain access to user’s private data without the appropriate permission. Hackers frequently replace any fake data with actual data. As a result, data security has recently generated a lot of attention. To provide access rights of files, the cloud computing is only option for authorized user. To overcome from security threats, a security model is proposed for cloud computing to enhance the security of cloud data through the fingerprint authentication for access control and genetic algorithm is also used for encryption/decryption of cloud data. To search desired data from cloud, fuzzy encrypted keyword search technique is used. The encrypted keyword is stored in cloud storage using SHA256 hashing techniques. The proposed model minimizes the computation time and maximizes the security threats over the cloud. The computed results are presented in the form of figures and tables.

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