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Hybrid Methods for Increasing Security of IoT and Cloud Data

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Machine Vision and Augmented Intelligence

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1007))

Abstract

There has been a boom in the amount of data that is being transferred over the Internet. With the growth of IoT and various cloud services, it can be said that the growth of this ever-increasing flow of data will be exponential in future. Several new high-speed communication media, like optical fiber cables, are being used for faster transfer of data with higher speeds. However, there is a need to secure all the data. Especially, data from IoT devices as they usually communicate wirelessly because of their ad hoc placements which varies per individual needs. The data collected can be sensitive and hence must be secured. Same can be said for the cloud services. The data from cloud server may be routed via various different types of networks. The security of these networks cannot be guaranteed. Instead, there is a need to make sure that the data remains secured even when it is traveling through unsecure networks. Here, a new hybrid encryption algorithm is proposed which uses AES, Blowfish, and ECC combined to enhance security while still remaining time and space efficient so that it can work on relatively low powered IoT devices too.

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Correspondence to Sunil Kumar .

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© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

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Mahajan, K., Kumar, S., Kumar, D. (2023). Hybrid Methods for Increasing Security of IoT and Cloud Data. In: Kumar Singh, K., Bajpai, M.K., Sheikh Akbari, A. (eds) Machine Vision and Augmented Intelligence. Lecture Notes in Electrical Engineering, vol 1007. Springer, Singapore. https://doi.org/10.1007/978-981-99-0189-0_45

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  • DOI: https://doi.org/10.1007/978-981-99-0189-0_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-0188-3

  • Online ISBN: 978-981-99-0189-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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