Security Framework for the Internet of Things Applications

The text highlights a comprehensive survey that focuses on all security aspects and challenges facing the Internet of Things systems, including outsourcing techniques for partial computations on edge or cloud while presenting case studies to map security challenges. It further covers three security aspects including Internet of Things device identification and authentication, network traffic intrusion detection, and executable malware files detection.

This book:

• Presents a security framework model design named Behavioral Network Traffic Identification and Novelty Anomaly Detection for the IoT Infrastructures.
• Highlights recent advancements in machine learning, deep learning, and networking standards to boost Internet of Things security.
• Builds a near real-time solution for identifying Internet of Things devices connecting to a network using their network traffic traces and providing them with sufficient access privileges.
• Develops a robust framework for detecting IoT anomalous network traffic.
• Covers an anti-malware solution for detecting malware targeting embedded devices.

It will serve as an ideal text for senior undergraduate and graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Salma Abdalla Hamad is currently an Information Security Manager at a Financial firm. She received a Ph.D. degree in computer science from Macquarie University in 2021. She worked under the supervision of Prof. Michael Sheng and Dr. Wei Emma Zhang. Salma obtained her Bachelor’s and Master’s de- grees in Electronics and Communication Engineering from Arab Academy for Science, Technology, and Maritime Transport, Egypt with distinctions in 2005 and 2009, respectively. Salma also possesses 17+ years of working experience in both the government sector and the financial sector, where she executed several projects pertinent to Information Security. Her research interests are concentrated in the domain of Information Security, more specifically, for the Internet of Things, Smart Cities, and Smart Homes.

Quan Z. Sheng is a full Professor and Head of the Department of Comput- ing at Macquarie University, Sydney, Australia. His research interests include the Internet of Things, service-oriented computing, distributed computing, Internet computing, and pervasive computing. Michael holds a Ph.D. degree in computer science from the University of New South Wales (UNSW) and did his post-doc as a research scientist at CSIRO ICT Centre.

Prof Michael Sheng is the recipient of the AMiner Most Influential Scholar in IoT Award in 2019, ARC Future Fellowship in 2014, Chris Wallace Award for Outstanding Research Contribution in 2012, and Microsoft Fellowship in 2003.

Wei Emma Zhang is currently a lecturer at the School of Computer Science, at the University of Adelaide. Her research interests include the Internet of Things, text mining, data mining, and knowledge base. She received a Ph.D. degree in computer science from the University of Adelaide in 2017. She has authored and co-authored more than 50 papers so far. She has also served on various conference committees and international journals in different roles such as track chair, proceeding chair, PC member, and reviewer. She is a member of the IEEE and ACM.