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Title	Privacy Preserving And Performance Improvement In Edgecomputing Using Machine Learning
ID_Doc	43116
Authors	Bhadauria S.; Kumar M.; Singh N.P.
Year	2022
Published	2022 IEEE Global Conference on Computing, Power and Communication Technologies, GlobConPT 2022
DOI	http://dx.doi.org/10.1109/GlobConPT57482.2022.9938248
Abstract	With the increase in the usage of IoT and mobile devices in our day to day lives results in generating vast amount of data, as well as increase in advanced services and applications such as VR, augmented reality and a race for building smart cities made it a challenging situation for cloud computing in terms of latency, privacy and scalability to resolve all these challenges edge computing falls into play as a modern model of computing where computing and storage are located closer to the data center, allowing a new latency and bandwidth-sensitive application class where data is processed at the nearer edge without sending it to the cloud [9]. The goal of this study is to implement an effective and safe proactive strategy (instead of sending a response of a query to each node, node should have its own local computational resources that updates the parameter to the central server) on edge devices which will provide more privacy, as personal data are processed at the nearest edge that can be leaked or exploited by any intruder and because of latency problem in the centralized approach there is a need for effective decentralized system, which additionally should give better outcome as off-base outcome can at some point be calamitous, like in the case of auto-driving car. We will also be presenting how we can utilize numerous encryption technique to scramble data for model training which regardless of whether get hacked by an intruder would be of no use, as if confidential data learned by the model or leaked to an intruder might lead to a significant loss. The proposed method would be tested to all the machine learning problems like word suggestion, image classification and many more. © 2022 IEEE.
Author Keywords	component; formatting; insert; style; styling

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