Abstract
One problem with the Internet of Things (IoT) is that user data and identities could be used in ways that aren’t what they were meant to be used for. Researchers have come up with different ways to lower privacy risks. But most of the existing solutions still have problems. They also have heavy cryptosystems and policies that are applied on both sensor devices and in the cloud. To solve these privacy problems, fog computing has been added to the edges of IoT networks to help with low latency, computation, and storage. This research uses deep learning models and hashing techniques that give the properties of User validation, Data confidentiality, Data verifiability, and Data integrity, and Data obfuscation that are done using MQTT protocol which derives more confidentiality, making data obscure. The future scope will be applied to AI models which can optimise the setup time for learning and training classification models.
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Kumar, R.A., Rekha, G., Vinuthna, K. (2023). A Novel Approach for Privacy Preserving Technique in IoT Fog and Cloud Environment. In: Raj, J.S., Perikos, I., Balas, V.E. (eds) Intelligent Sustainable Systems. ICoISS 2023. Lecture Notes in Networks and Systems, vol 665. Springer, Singapore. https://doi.org/10.1007/978-981-99-1726-6_10
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DOI: https://doi.org/10.1007/978-981-99-1726-6_10
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