A Novel Blockchain-Assisted Deep Learning Model For Secure Edge Intelligence in IoT Networks

The Internet is being connected to billions of mobile and Internet of Things (IoT) devices, generating zillions of Bytes of data at the network edge. This is in addition to developments in mobile computing and the Internet of Things (IoT). In the context of edge computing, applications are placed closer to data sources such as IoT sensors, local edge devices, and edge servers. Data are transmitted from edge devices to dedicated computer infrastructures for a range of activities in any edge computing environment. For the reason that data are regularly sent from IoT edge devices to centralized virtualization technologies, it is more vulnerable to security vulnerabilities and complexity measures. Finally, to preserve the privacy of the IoT devices, the performance of the proposed algorithms is evaluated using datasets in a large-scale network prototyped system. According to the data, the suggested strategy is both more effective and secure than the alternatives.