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- W4205616393 abstract "AbstractFor pervasive applications of the artificial neural networks (ANN), the autonomous control usually affects the overall processing and analysis of data in the healthcare systems. Though, involvement of several malicious activities by the intruders may drastically affect the overall communication system. Recently, more and more engineers have applied a trusted and secure Artificial Internet of Things (AIoT) healthcare system is used to analyze and process the accurate control for overall benefits. However, the lack of security and trust in IoT devices results in accidental control of risks. The aim of this chapter is to propose an ANN-based secure network to analyze the legitimacy of IoT devices by categorizing through back propagation and Bayesian rule schemes. The proposed system can efficiently recognize the illegal activity of malicious IoT devices used to record, manage, and store the sensitive information of healthcare centers. The proposed phenomenon is proposed over various security metrics against conventional scheme. Further, we have discussed the Software-Defined Networks (SDNs) architectures that provide better solutions by removing the decision making capabilities from intermediate nodes in the network.KeywordsArtificial intelligenceArtificial Internet of ThingsArtificial neural network (ANN)Secure ANNSecurity protocolsANN-based healthcare systemBack propagationBayesian ruleIoT devicesSoftware-defined networks (SDNs)" @default.
- W4205616393 created "2022-01-26" @default.
- W4205616393 creator A5077775180 @default.
- W4205616393 date "2021-10-08" @default.
- W4205616393 modified "2023-09-25" @default.
- W4205616393 title "Trusted Mechanism Using Artificial Neural Networks in Healthcare Software-Defined Networks" @default.
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- W4205616393 doi "https://doi.org/10.1007/978-3-030-89328-6_12" @default.
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