Mohammad Alshehri is a PhD Candidate and Academic Staff Member at the School of Software, Faculty of Engineering & IT at University of Technology Sydney (UTS), Australia. He received his master’s degree in Information Technology from Faculty of Engineering & IT at University of Technology Sydney (UTS), Australia and he obtained his bachelor’s degree with second honor in Computer Science from King Khalid University, Saudi Arabia.
His main research interest lies in the areas of Cyber Security, Trust and Trust Management for the Internet of Things (IoT).
He was awarded the Academic Excellence Award from Saudi Arabia Cultural Attaché, Canberra, Australia.
- Technical Committee Program Member for The 2nd EAI International Conference on Future Intelligent Vehicular Technologies in 2017
- Chair of IEEE UTS Student Branch in 2016.
- Chair a Session for The 22nd International Conference on Neural Information Processing (ICONIP2015) in 2015.
- Member of Centre Artificial Intelligence (CAI) at UTS
- Member of IEEE.
- Internet of Things (IoT)
- Trust Management
- Trust-Based Clustering
- Cyber Security Attacks
- 42904 - Cloud Computing and Software as a Service
- 32555 - Fundamentals of Software Development
- 32144 - Technology Research Preparation (Professional Stream)
- 32144 - Technology Research Preparation (Research Stream)
- 32933 - Research Project (A Master Degree Research Project Supervision)
© 2018, Springer-Verlag GmbH Austria, ein Teil von Springer Nature. Recently, the Internet of things (IoT) has received a lot of attention from both industry and academia. A reliable and secure IoT connection and communication is essential for the proper working of the IoT network as a whole. One of the ways to achieve robust security in an IoT network is to enable and build trusted communication among the things (nodes). In this area, the existing IoT literature faces many critical issues, such as the lack of intelligent cluster-based trust approaches for IoT networks and the detection of attacks on the IoT trust system from malicious nodes, such as bad service providers. The existing literature either does not address these issues or only addresses them partially. Our proposed solution can firstly detect on-off attacks using the proposed fuzzy-logic based approach, and it can detect contradictory behaviour attacks and other malicious nodes. Secondly, we develop a fuzzy logic-based approach to detect malicious nodes involved in bad service provisioning. Finally, to maintain the security of the IoT network, we develop a secure messaging system that enables secure communication between nodes. This messaging system uses hexadecimal values with a structure similar to serial communication. We carried out extensive experimentation under varying network sizes to validate the working of our proposed solution and also to test the efficiency of the proposed methods in relation to various types of malicious behavior. The experiment results demonstrate the effectiveness of our approach under various conditions.
Alshehri, MD, Hussain, F & Hussain, O 2018, 'Clustering-Driven Intelligent Trust Management Methodologyfor the Internet of Things (CITM-IoT)', Mobile Networks and Applications, vol. 23, no. 3, pp. 419-431.View/Download from: UTS OPUS or Publisher's site
The growth and adoption of the Internet of Things (IoT) is increasing day by day. The large number of IoT devices increases the risk of security threats such as (but not limited to) viruses or cyber-attacks. One possible approach to achieve IoT security is to enable a trustworthy IoT environment in IoT wherein the interactions are based on the trust value of the communicating nodes. Trust management and trust assessment has been extensively studied in distributed networks in general and the IoT in particular, but there are still outstanding pressing issues such as bad-mouthing of trust values which prevent them from being used in practical IoT applications. Furthermore, there is no research in ensuring that the developed IoT trust solutions are scalable across billions of IoT nodes. To address the above-mentioned issues, we propose a methodology for scalable trust management solution in the IoT. The methodology addresses practical and pressing issues related to IoT trust management such as trust-based IoT clustering, intelligent methods for countering bad-mouthing attacks on trust systems, issues of memory-efficient trust computation and trust-based migration of IoT nodes from one cluster to another. Experimental results demonstrate the effectiveness of the proposed approaches.
Alsinglawi, BS, Nguyen, QV, Gunawardana, U, Simoff, S, Maeder, A, Alshehri, M & Elkhodr, M 2019, 'Passive RFID Localization in the Internet of Things' in Recent Trends and Advances in Wireless and IoT-enabled Networks, Springer.
Smart home researches have emerged in recent years as a popular field of study in pervasive computing to suggest a solution that can be beneficial for impaired individuals and elderly on their daily life basis. Location tracking accuracy is a major research challenge in smart homes that needs much further investigation. This paper presents a review of the existing techniques and technologies in location-based systems in the Internet of things, and it identifies the research gap of localization in smart home settings. The paper proposes a localization framework for smart home healthcare as well as our preliminary implementation of the localization framework.
Alshehri, M & Hussain, F 2019, 'A Distributed Trust Management Model for the Internet of Things (DTM-IoT)' in Recent Trends and Advances in Wireless and IoT-enabled Networks, Springer.View/Download from: Publisher's site
The Internet of Things (IoT) is a paradigm that facilitates autonomous communications among various IoT devices with minimal human intervention. This raises many security challenges, which are critical and must be addressed to allow for the wide deployment of IoT. Trust must be provisioned among the various heterogeneous IoT devices. In this paper, a distributed trust management model is proposed. The model offers solutions to trust management and negotiations in the IoT. It is inspired by clustering techniques that are adopted in WSNs. After introducing the structural design and the main components of the trust model, we demonstrate how our new approach supports trust negotiations and management in the IoT.
Elkhodr, M, Alsinglawi, B & Alshehri, M 2018, 'A Privacy Risk Assessment for the Internet of Things in Healthcare' in Applications of Intelligent Technologies in Healthcare, Springer.
This book covers topics related to medical practices from communications technology point of view. The book provides detailed inside information about the use of health informatics and emerging technologies for the well-being of patients.
Alshehri, M, Elkhodr, M & Alsinglawi, B 2018, 'Data Provenance in the Internet of Things', International Conference on Advanced Information Networking and Applications Workshops, IEEE, Krakow, Poland, Poland.View/Download from: UTS OPUS or Publisher's site
There is a need to create a trusted and secure IoT environment to share information, create knowledge and perform digital transactions. Trustworthy data collection, mining and fusion is vital for the successful widespread acceptance of IoT applications. This requires not only accurate, secure, and precise data collection; but also provisioning of data provenance throughout the whole life cycle of the IoT device. To this end, this paper introduces a provenance-based trust management solution which helps in establishing a trust relationship among communicating devices in the IoT. This work extends the Internet of Things Management Platform (IoT-MP) by assuring data provenance. Thus complementing the previous IoT-MP capabilities in preserving the privacy of users in the IoT.
Alshehri, MD & Hussain, F 2017, 'A Centralized Trust Management Mechanism for the Internet of Things (CTM-IoT)', Advances on Broad-Band Wireless Computing, Communication and Applications, International Conference on Broad-Band Wireless Computing, Communication and Applications, Springer, Barcelona, Spain, pp. 533-543.View/Download from: UTS OPUS or Publisher's site
The Internet of Things (IoT) is an extended network that allows all devices to be connected to one another over the Internet. This new network faces numerous challenges, but mainly security issues. One such issue is how the IoT's nodes can trust each other when they are connected over the Internet. There is a lack of studies that address the issue of trust management in IoT, or that provide a fully trustworthy framework. This paper proposes and delivers a centralized trust management mechanism for IoT by adding trust modules as a feature of the central trust manager, the Super Node (SN). To deliver a comprehensive approach, the SN includes other modules which are integrated with the whole IoT Trust Management framework to provide trustworthy communication between all nodes.
Alshehri, MD & Hussain, FK 2015, 'A comparative analysis of scalable and context-aware trust management approaches for internet of things', Neural Information Processing (LNCS), Part iV, International Conference on Neural Information Processing, Springer, Istanbul, TURKEY, pp. 596-605.View/Download from: UTS OPUS or Publisher's site
© Springer International Publishing Switzerland 2015. The Internet of Things - IoT - is a new paradigm in technology that allows most physical 'things' to contact each other. Trust between IoT devices is a critical factor. Trust in the IoT environment can be modeled using various approaches, such as confidence level and reputation parameters. Furthermore, trust is an important element in engineering reliable and scalable networks. In this paper, we survey scalable and context-aware trust management for IoT from three perspectives. First, we present an overview of the IoT and the importance of trust in relation to it, and then we provide an in-depth trust/reliable management protocol for the IoT and evaluate comparable trust management protocols. We also investigate a scalable solution for trust management in the IoT and provide a comparative evaluation of existing trust solutions. We then pre-sent a context-aware assessment for the IoT and compare the different trust solutions. Lastly, we give a full comparative analysis of trust/reliability management in the IoT. Our results are drawn from this comparative analysis, and directions for future research are outlined.
Ikram, MA, Alshehri, MD & Hussain, FK 2015, 'Architecture of an IoT-based System for Football Supervision (IoT Football)', Proceedings of the 2015 IEEE 2nd World Forum on Internet of Things (WF-IoT), IEEE World Forum on Internet of Things (WF-IoT), IEEE, Milan, Italy, pp. 69-74.View/Download from: UTS OPUS or Publisher's site
Football, also called soccer, is one of the most popular sports in the world, if one considers the number of fans as well as the number of players. However, footballers face serious injuries during the match and even during training. Concussion, hypoglycemia, swallowing the tongue and shortness of breath are examples of the health problems footballers face, and in extreme cases, may lead to death. In addition, many sport clubs and sport academies spend millions of dollars contracting new professional footballers or even developing new professional footballers. The Internet of Things (IoT) is a new paradigm that combines various technologies to enhance our lives. Today's technology can protect footballers by diagnosing any health problems, which may occur during the match or training session, which, if detected early, may prevent any adverse effects on their long-term health. This paper proposes an IoT-based architecture for the sport of football, called IoT Football. Our proposal aims to embed sensing devices (e.g. sensors and RFID), telecommunication technologies (e.g. ZigBee) and cloud computing in the sport of football in order monitor the health of footballers and reduce the occurrence of adverse health conditions. The aim is to integrate the IoT environment, in particular the IoT application, into the field of sport in the form of a new application.