A survey on Deep Learning Methodologies for Internet of Things (IoT) Security

Abstract

Internet of things is the term coined for all the devices that are connected and can exchange data.
With the advent in technology, growth of the IOT industry has become extensive. IOT universe has
made it possible for users to remotely monitor their network connected devices. However, IoT systems
comprising Wireless Sensor Networks (WSNs), Radio Frequency Identifications (RFIDs), and cloud
computing are exposed to numerous data privacy and security threats including intrusions, Denial of
Service (DoS) attacks, spoofing attacks, Distributed Denial of Service (DDoS) attacks, malwares,
jamming, eavesdropping amongst others[7].The larger number of the present day security solutions
proliferate heavy computation and communication load for IoT devices, Most of the outdoor nodes
and devices do not have high security protocols which make them highly susceptible to attacks.The
review focuses on providing solution by implementing deep learning techniques to tackle the
discussed issues.