Deep Learning Fusion to Attack Detection for Internet of Things Communications

 Ossama Embarak ^*1, Mhmed Algrnaodi²

¹ Higher Colleges of Technology (HCT), UAE

² Electrical Engineering Department, Ecole de technologie superieure, Montreal, Canada

Emails: oembarak@hct.ac.ae ; mhmed.algrnaodi.1@ens.etsmtl.ca

Abstract

The increasing deep learning techniques used in multimedia and network/IoT solve many problems and increase performance. Securing the deep learning models, multimedia, and network/IoT has become a major area of research in the past few years which is considered to be a challenge during generative adversarial attacks over the multimedia or network/IoT. Many efforts and studies try to provide intelligent forensics techniques to solve security issues. This paper introduces a holistic organization of intelligent multimedia forensics that involve deep learning fusion, multimedia, and network/IoT forensics to attack detection. We highlight the importance of using deep learning fusion techniques to obtain intelligent forensics and security over multimedia or Network/IoT. Finally, we discuss the key challenges and future directions in the area of intelligent multimedia forensics using deep learning fusion techniques.

Keywords: Deep Learning Fusion; IoT; Network; Multimedia; Attack Detection.