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Hybrid Encryption Technique for Securing Cloud Data

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Cryptology and Network Security with Machine Learning (ICCNSML 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 918))

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Abstract

The present research raises few concerns that are arising due to security in cloud computing. As we know several trades are shifting from conventional storage of facts to cloud-enabled storages, it suggests an operative techniques of data access at all times and locations, respectively. Yet, security of the data is one of the foremost concerns, it prevents the establishment to make use of use cloud computing for their existing challenges. A hybrid security system based on some cryptography technique was proposed in this paper. The proposed hybrid model is the amalgamation of techniques based upon symmetric and asymmetric key model. In the present research, the implementation of various techniques of AES and ECC was incorporated which raised the safety of data by incorporating numerous levels of security concerns at both the ends, i.e., sender and receiver, respectively. To lessen the dangers to security of data, the present security standard offers the high level of transparent behavior with respect to users of cloud as well as service providers. The proposed model was implemented by making the use of technologies like Java and the cloud-sim. The cloud-sim and Java were used to implement the suggested model. This methodology increases data security to a greater degree while speeding up text file uploads and downloads in contrast to the current system.

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Correspondence to Mamta Joshi .

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Joshi, M., Priya, R., Joshi, M. (2024). Hybrid Encryption Technique for Securing Cloud Data. In: Chaturvedi, A., Hasan, S.U., Roy, B.K., Tsaban, B. (eds) Cryptology and Network Security with Machine Learning. ICCNSML 2023. Lecture Notes in Networks and Systems, vol 918. Springer, Singapore. https://doi.org/10.1007/978-981-97-0641-9_9

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  • DOI: https://doi.org/10.1007/978-981-97-0641-9_9

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-97-0640-2

  • Online ISBN: 978-981-97-0641-9

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