Applications of Machine Learning and Deep Learning in Securing Internet of Battlefield Things: A Futuristic Perspective

The Internet of Battlefield Things (IoBT) is an integrated, highly vulnerable network of interconnected battlefield devices. An IoBT network is considerably more vulnerable than any other IoT network and becomes more dangerous regarding soldiers' lives and the nation's confidential information. Even though the security of IoT applications is broadly studied, IoBT was completely neglected until 2016, when the U.S. Army first highlighted the concept of IoBT. This paper presents the first IoBT system model with major challenges an IoBT ecosystem can face. Even though IoBT is obscure, it can play a key role in the real-time battlefield. This paper analyzes and discloses the applications of Machine Learning (ML) and Deep Learning (DL) methods for the IoBT ecosystem. To our knowledge, this is the first study focusing on discovering ML/DL applications in IoBT security. This article will help numerous researchers to identify and implement applications of ML/DL in the IoBT field.