Fadi Farha

Bio: Fadi Farha is an academic researcher from University of Science and Technology Beijing. The author has contributed to research in topics: Computer science & Ubiquitous computing. The author has an hindex of 6, co-authored 20 publications receiving 143 citations.

Review on Smart Gas Sensing Technology.

Abstract: With the development of the Internet-of-Things (IoT) technology, the applications of gas sensors in the fields of smart homes, wearable devices, and smart mobile terminals have developed by leaps and bounds. In such complex sensing scenarios, the gas sensor shows the defects of cross sensitivity and low selectivity. Therefore, smart gas sensing methods have been proposed to address these issues by adding sensor arrays, signal processing, and machine learning techniques to traditional gas sensing technologies. This review introduces the reader to the overall framework of smart gas sensing technology, including three key points; gas sensor arrays made of different materials, signal processing for drift compensation and feature extraction, and gas pattern recognition including Support Vector Machine (SVM), Artificial Neural Network (ANN), and other techniques. The implementation, evaluation, and comparison of the proposed solutions in each step have been summarized covering most of the relevant recently published studies. This review also highlights the challenges facing smart gas sensing technology represented by repeatability and reusability, circuit integration and miniaturization, and real-time sensing. Besides, the proposed solutions, which show the future directions of smart gas sensing, are explored. Finally, the recommendations for smart gas sensing based on brain-like sensing are provided in this paper.

Artificial intelligence in cyber security: research advances, challenges, and opportunities

Abstract: In recent times, there have been attempts to leverage artificial intelligence (AI) techniques in a broad range of cyber security applications. Therefore, this paper surveys the existing literature (comprising 54 papers mainly published between 2016 and 2020) on the applications of AI in user access authentication, network situation awareness, dangerous behavior monitoring, and abnormal traffic identification. This paper also identifies a number of limitations and challenges, and based on the findings, a conceptual human-in-the-loop intelligence cyber security model is presented.

IoT-Enabled Social Relationships Meet Artificial Social Intelligence

Abstract: With the recent advances of the Internet of Things, and the increasing accessibility to ubiquitous computing resources and mobile devices, the prevalence of rich media contents, and the ensuing social, economic, and cultural changes, computing technology and applications have evolved quickly over the past decade. They now go beyond personal computing, facilitating collaboration and social interactions in general, causing a quick proliferation of social relationships among IoT entities. The increasing number of these relationships and their heterogeneous social features have led to computing and communication bottlenecks that prevent the IoT network from taking advantage of these relationships to improve the offered services and customize the delivered content, known as social relationships explosion. On the other hand, the quick advances in artificial intelligence applications in social computing have led to the emerging of a promising research field known as Artificial Social Intelligence (ASI) that has the potential to tackle the social relationships explosion problem. This paper discusses the role of IoT in social relationships management, the problem of social relationships explosion in IoT, and reviews the proposed solutions using ASI, including social-oriented machine-learning and deep-learning techniques.

SRAM-PUF-Based Entities Authentication Scheme for Resource-Constrained IoT Devices

Abstract: With the development of the cloud-based Internet of Things (IoT), people and things can request services, access data, or control actuators located thousands of miles away. The entity authentication of the remotely accessed devices is an essential part of the security systems. In this vein, physical unclonable functions (PUFs) are a hot research topic, especially for generating random, stable, and tamper-resistant fingerprints. This article proposes a lightweight, robust static random access memory (SRAM)-PUF-based entity authentication scheme to guarantee that the accessed end devices are trustable. The proposed scheme uses challenge-response pairs (CRPs) represented by reordered memory addresses as challenges and the corresponding SRAM cells’ startup values as responses. The experimental results show that our scheme can efficiently authenticate resources-constrained IoT devices with a low computation overhead and small memory capacity. Furthermore, we analyze the SRAM-PUF by testing the PUF output under different environmental conditions, including temperature and magnetic field, in addition to exploring the effect of writing different values to the SRAM cells on the stability of their startup values.

Is Metaverse in education a blessing or a curse: a combined content and bibliometric analysis

Abstract: Abstract The Metaverse has been the centre of attraction for educationists for quite some time. This field got renewed interest with the announcement of social media giant Facebook as it rebranding and positioning it as Meta. While several studies conducted literature reviews to summarize the findings related to the Metaverse in general, no study to the best of our knowledge focused on systematically summarizing the finding related to the Metaverse in education. To cover this gap, this study conducts a systematic literature review of the Metaverse in education. It then applies both content and bibliometric analysis to reveal the research trends, focus, and limitations of this research topic. The obtained findings reveal the research gap in lifelogging applications in educational Metaverse. The findings also show that the design of Metaverse in education has evolved over generations, where generation Z is more targeted with artificial intelligence technologies compared to generation X or Y. In terms of learning scenarios, there have been very few studies focusing on mobile learning, hybrid learning, and micro learning. Additionally, no study focused on using the Metaverse in education for students with disabilities. The findings of this study provide a roadmap of future research directions to be taken into consideration and investigated to enhance the adoption of the Metaverse in education worldwide, as well as to enhance the learning and teaching experiences in the Metaverse.

Secure Healthcare Data Aggregation and Transmission in IoT—A Survey

Abstract: Internet of medical things (IoMT) is getting researchers’ attention due to its wide applicability in healthcare Smart healthcare sensors and IoT enabled medical devices exchange data and collaborate with other smart devices without human interaction to securely transmit collected sensitive healthcare data towards the server nodes Alongside data communications, security and privacy is also quite challenging to securely aggregate and transmit healthcare data towards Fog and cloud servers We explored the existing surveys to identify a gap in literature that a survey of fog-assisted secure healthcare data collection schemes is yet contributed in literature This paper presents a survey of different data collection and secure transmission schemes where Fog computing based architectures are considered A taxonomy is presented to categorize the schemes Fog assisted smart city, smart vehicle and smart grids are also considered that achieve secure, efficient and reliable data collection with low computational cost and compression ratio We present a summary of these scheme along with analytical discussion Finally, a number of open research challenges are identified Moreover, the schemes are explored to identify the challenges that are addressed in each scheme