A Review on Machine Learning Based Security in Edge Computing Environment

One of the major breakthrough technologies that can revolutionize different enterprises and institutions aiming to overcome the existing constraints of conventional cloud-based networks is Edge Computing (EC). Large number of sensors can be connected through it and it can also deliver services as per user requirement at the device end. Security is a big challenge despite the fact that EC offers end-to-end connection, accelerates operations, and minimizes data transmission latency. Due to the augmentation in uses of Edge Devices and generation of significant amount of confidential information at the IoT devices (hardware including machines, appliances, gadgets and other sensors) as well as in the cloud in our daily lives, it is important that static and mobile data are protected with utmost priority. The many forms of threats that the intrusion detection systems as well as the Edge network face are covered in detail in this article. The remaining section of the article covers the implementation difficulties for present Edge network security techniques as well as discusses potential future research scopes.