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- W4224882708 abstract "The Internet of Things is quickly becoming a pervasive computer service that requires massive data storage and processing. Unfortunately, because of resource restrictions, self-organization, and the specific characteristics of short-distance communication in IoT. Deep Learning (DL) approaches can be used to solve a variety of security issues. A deep learning model is provided here to increase IoT security. Overall, the research reveals that using Deep Learning to implement security measures such as authentication, authentication, Hardware Device Integrity Testing, and confidentiality for IoT devices and their inherent weaknesses is useless. As a result, existing security approaches need be upgraded in order to ensure the viability of the IoT ecosystem. In terms of security, we look at how deep learning can help IoT systems be more secure. Finally, we assess deep learning’s system security in IoT systems." @default.
- W4224882708 created "2022-04-27" @default.
- W4224882708 creator A5052121556 @default.
- W4224882708 creator A5086506367 @default.
- W4224882708 date "2022-03-25" @default.
- W4224882708 modified "2023-09-29" @default.
- W4224882708 title "Deep Learning Model to Improve Security in IOT Systems" @default.
- W4224882708 doi "https://doi.org/10.1109/icstsn53084.2022.9761347" @default.
- W4224882708 hasPublicationYear "2022" @default.
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