Ephemeral Resilient Signcryption and Piecewise Deep Belief Network forReliable with QoS aware Streaming Social Media Data Transmissionin 5G Network
Keywords:5G technology, social network, reliable and Qos aware streaming data transmission, Piecewise regressive Damped Convolutional deep belief network, ephemeral resilient matching schnorrsigncryption
Fifth Generation Mobile Network (5G) is supported by wireless network services to offer extensive data transmission to improve device-to-device transportation quality, as well as minimize working costs. It allows users to seamlessly access a variety of multimedia services in social network platforms such as live streaming applications like Internet live sports networks, youtube, Facebook, etc... There are various security and privacy issues related to the user’s shared multimedia information. With the fast-growing 5G technology, privacy preservation of streaming data transmission in social network platforms plays a vital role for handling the attackers. In order to improve the QoS aware secure streaming data transmission in a 5G network, a novel technique called Ephemeral Resilient SchnorrSigncryptive Piecewise Damped Convolutional Deep Belief Network (ERSSPDCDBN) is introduced with higherreliability. The ERSSPDCDBN technique first collects the social media stream data. After that, secure data transmission is performed by applying an ephemeral resilient schnorrsigncryption. For enhancing security, ephemeral resilient key generation, signcryption, and unsigncryptionis carried out by using signcryption method. Followed by, the user authenticity is verified based on digital signature verification using a simple matching coefficient. If the signature is valid, the authorized user obtains the original data and avoids the attackers. During data transmission, Piecewise regressive Damped Convolutional deep belief network is developed for achieving higher throughput and minimum latency. Experimental of ERSSPDCDBN is conducted by using six metrics.
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