Review
Computer Science, Information Systems
Omer Aslan, Semih Serkant Aktug, Merve Ozkan-Okay, Abdullah Asim Yilmaz, Erdal Akin
Summary: Internet usage has grown exponentially, with individuals and companies performing multiple daily transactions in cyberspace rather than in the real world. The pandemic has accelerated this process. As a result, traditional crimes have shifted to the digital space.
Article
Computer Science, Hardware & Architecture
N. Renya Nath, Hiran Nath
Summary: The Internet of Things (IoT) is revolutionizing the global economy and society. However, its wide adoption also brings new security and privacy challenges. In order to build efficient and secure IoT systems, a thorough understanding of potential threats and vulnerabilities is necessary.
COMPUTERS & ELECTRICAL ENGINEERING
(2022)
Article
Computer Science, Information Systems
Hamza Aldabbas, Rashid Amin
Summary: The Internet of Things (IoT) is a network of devices used for various tasks, utilizing a traditional networking paradigm where the control and data planes are vertically integrated. Software Defined Networking (SDN) separates the control plane from the data plane, making network management easier. Network operators prioritize system security by deploying new devices in SDN architecture to control ARP spoofing attacks.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Tian Xie, Guan-Hua Tu, Chi-Yu Li, Chunyi Peng
Summary: There are disparities in service charging between IoT and non-IoT devices which may lead to security issues. Researchers identified four security vulnerabilities and developed an anti-abuse solution to mitigate attack incentives.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2021)
Review
Computer Science, Artificial Intelligence
Laraib Sana, Muhammad Mohsin Nazir, Muddesar Iqbal, Lal Hussain, Amjad Ali
Summary: The Internet of Things (IoT) is a rapidly growing technology with increasing concerns over privacy and cyber-security. This study aims to improve IoT security through deep learning methods for intrusion and anomaly detection, based on data transformation analysis of IoT datasets. By conducting a systematic literature review (SLR), this study identifies various datasets, performance metrics, features, preprocessing techniques, and methods/models used in IoT analysis, highlighting the need for further enhancements and identification of cyber-security issues.
APPLIED ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Theory & Methods
Shu-Yu Kuo, Fan-Hsun Tseng, Yao-Hsin Chou
Summary: The Metaverse has the potential to drive the development of new technologies. However, there is a need to address the security concerns surrounding the Metaverse, particularly in detecting malware. Wormhole attacks pose a significant threat in mobile cloud and Metaverse environments, and current detection methods have limitations. Research is focused on developing a novel defense mechanism against wormhole attacks.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2023)
Article
Engineering, Electrical & Electronic
Hakan Alakoca, Mustafa Namdar, Sultan Aldirmaz-Colak, Mehmet Basaran, Arif Basgumus, Lutfiye Durak-Ata, Halim Yanikomeroglu
Summary: This article discusses the importance of physical layer security of reconfigurable intelligent surfaces (RIS) in 6G wireless systems. The study focuses on potential vulnerabilities and malicious attacks, including metasurface manipulation attacks (MSMA) and eavesdropping booster-based MSMA (EaB-MSMA). The performance degradation and loss of secrecy capacity in these attacks are also evaluated.
IEEE COMMUNICATIONS MAGAZINE
(2023)
Review
Computer Science, Hardware & Architecture
Shubhankar Chaudhary, Pramod Kumar Mishra
Summary: This paper investigates the issue of DDoS attacks in IIoT and discusses the solutions, as well as the correlation between IoT, IIoT, and various communication layers. It also explores research in fields such as machine learning, deep learning, federated learning, and transfer learning.
Article
Computer Science, Information Systems
Rami J. Alzahrani, Ahmed Alzahrani
Summary: The rapid development of IoT technology has brought new services and applications for users, but also challenges in terms of network anomalies. This research employs deep learning and machine learning algorithms to achieve high accuracy in DDoS intrusion detection.
Article
Chemistry, Multidisciplinary
Ibrahim S. Alsukayti, Mohammed Alreshoodi
Summary: This research presents an extensive experimental study on critical RPL routing attacks considering simple-to-complex attack scenarios in varying-scale RPL network setups. The results indicate the adverse impacts of routing attacks on the overall performance of RPL networks. Even in simple attack scenarios, the attacked networks experienced noticeable degradation in QoS performance and topology stability, along with considerable increases in energy consumption and control traffic overhead. These impacts were more evident in large-scale experimental setups and also under composite and hybrid routing attacks.
APPLIED SCIENCES-BASEL
(2023)
Review
Oncology
Samantha J. J. Sadler, Erickson F. F. Torio, Alexandra J. J. Golby
Summary: This study aims to analyze global cancer surgery literature since 2015 and perform a SWOT analysis. A systematic search was conducted to identify relevant articles, and 46 articles were included for analysis. The findings highlighted various themes and challenges, including local epidemiologic studies, innovations and feasibility studies, prioritizing quality of life outcomes, multidisciplinary team approaches, limited resources, health system gaps, lack of economic analyses, diverse cancer management strategies, inter-setting collaboration, research expansion, the COVID-19 pandemic, and technological advancements.
Article
Economics
Bo Zhu, Yuanyue Deng, Xin Hu
Summary: The study examines the spillover effects in the risk networks of global energy firms, revealing significant impacts on national energy security. Domestic risk contagion dominates global security risks, while cross-border risk spillovers weaken the security performance of energy-importing countries. Energy production and end-use energy price serve as two influencing mechanisms through which risk contagion affects security issues.
Article
Automation & Control Systems
Liming Fang, Yang Li, Zhe Liu, Changchun Yin, Minghui Li, Zehong Jimmy Cao
Summary: The application of IoT in the medical field has brought unprecedented convenience but also security risks, leading to the proposal of an anomaly detection system for detecting illegal behavior (DIB) to ensure the safety of control services. The model based on rough set theory and FCVM can improve the accuracy of DIB classification anomalies.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Computer Science, Hardware & Architecture
Inam Ullah, Asra Noor, Shah Nazir, Farhad Ali, Yazeed Yasin Ghadi, Nida Aslam
Summary: The term Internet of Things (IoT) refers to a network that gathers, analyzes and modifies data from all connected devices to provide new services. IoT devices require a constant Internet connection, leading to rapid growth in data volume and speed. Ensuring IoT security is crucial to protect customer privacy, data integrity, and the security of assets and IoT devices. This research work aims to address security problems in IoT devices by organizing them into categories and evaluating various features.
JOURNAL OF SUPERCOMPUTING
(2023)
Article
Computer Science, Information Systems
Amit Kumar Sikder, Giuseppe Petracca, Hidayet Aksu, Trent Jaeger, A. Selcuk Uluagac
Summary: The increasing popularity of smart devices has raised concerns over security threats, particularly attacks that abuse sensors on these devices. Due to the lack of proper security mechanisms, smart devices are vulnerable to sensor-based attacks which can compromise device security and privacy.
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2021)
Article
Computer Science, Artificial Intelligence
B. D. Deebak, Fadi Al-Turjman
Summary: This paper introduces the application of S-USI in cloud-based healthcare systems and proposes a robust secure-based S-USI mechanism and a coexistence protocol proof for pervasive services in the cloud.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Fahim Ullah, Fadi Al-Turjman
Summary: Blockchain-based smart contracts are transforming the smart real estate sector in smart cities. This study explores the literature on blockchain smart contracts in smart real estate and proposes a conceptual framework for their adoption in smart cities. Through a systematic review of literature published between 2000 and 2020, ten key aspects of blockchain smart contracts are identified and organized into six layers. The study presents a decentralized application and its interactions with Ethereum Virtual Machine (EVM), along with a detailed design and interaction mechanism for real estate owners and users as parties to a smart contract. It also provides a stepwise procedure for establishing and terminating smart contracts, along with a list of functions for initiating, creating, modifying, or terminating a smart contract. The study has the potential to enhance the contracting process for users and create new business opportunities for real estate owners, property technologies companies, and real estate agents.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Software Engineering
Deebak Bakkiam Deebak, Fadi AL-Turjman
Summary: Proper real-time data processing and analysis are essential for Internet of Things (IoT) and cyber-physical systems, with the evolution of mobile edge computing addressing security and privacy issues. The integration of computing methods and communication technologies in healthcare systems improves medical services. A lightweight privacy-aware secure authentication (LPASA) scheme is proposed to protect vulnerable medical data, achieving better quality of services in resource-constrained environments.
CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Aditya Khamparia, Babita Pandey, Fadi Al-Turjman, Prajoy Podder
Summary: This article presents a computer aided detection system for early knee osteoarthritis and rheumatoid detection using X-ray images and machine learning classifiers. The CAD system can be used remotely to assist medical practitioners in treatments of knee arthritis. The presented results show commendable improvement over different existing feature extractors in combination with different classifiers.
Article
Computer Science, Artificial Intelligence
Abdullahi Umar Ibrahim, Pwadubashiyi Coston Pwavodi, Mehmet Ozsoz, Fadi Al-Turjman, Tirah Galaya, Joy Johnson Agbo
Summary: This article provides an overview of the characteristics, historical pandemics, and diagnostic methods of coronaviruses. It emphasizes the need for rapid, sensitive, simple, and affordable diagnostic tools for the virus, and introduces AI-driven and CRISPR-based approaches for diagnosis and treatment. The article also highlights limitations of laboratory techniques and open research issues in the field.
JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Information Systems
S. Ramesh, S. Nirmalraj, S. Murugan, R. Manikandan, Fadi Al-Turjman
Summary: The use of mobile devices and mobile applications have posed challenges to the infrastructure of mobile and wireless networking. This article proposes a method to handle the challenges of mobile sensor networks by providing secure and energy-efficient communication, enabling sensor node mobility and energy optimization.
JOURNAL OF SIGNAL PROCESSING SYSTEMS FOR SIGNAL IMAGE AND VIDEO TECHNOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Rajagopal Kumar, Fadi Al-Turjman, L. N. B. Srinivas, M. Braveen, Jothilakshmi Ramakrishnan
Summary: This paper proposes an Adaptive Neuro-fuzzy Inference System (ANFIS)-based machine learning technique to predict the possible outbreak of COVID-19 in India. The technique effectively tracks the growth of the epidemic and provides important information for public health control.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
S. D. Agashe, B. K. Lande, Vanita Jain, Gopal Chaudhary, Fadi Al-turjman
Summary: This paper proposes a new method for computing the optimal control, which steers the initial state of a system to a specified or unspecified point in the state space by minimizing a given performance index. The classical Calculus of Variations and the modern approach of variation in control that leads to Pontriagin's principle are compared. By deriving the maximum principle of Pontriagin using the classical Calculus of Variations modified with brief perturbation, an expression for the change in the value of performance index is obtained. Three examples are provided to demonstrate the feasibility of the derived methods.
Article
Automation & Control Systems
Arun Sekar Rajasekaran, Maria Azees, Fadi Al-Turjman
Summary: This paper provides a summary of V2G network characteristics, significance, security services, and challenges. It also offers an overview of various security attacks and related countermeasures to make V2G communications more secure.
JOURNAL OF CONTROL AND DECISION
(2023)
Article
Computer Science, Information Systems
Zahraa Tarik AlAli, Salah Abdulghani Alabady
Summary: In this study, a system is proposed to detect fires and the blood of injured people at disaster sites using images taken from unmanned aerial vehicles (UAVs). The system processes the images using color detection and edge detection filters in MATLAB, synthesizes the architecture using Excel DSP, and implements it on the FPGA using System Generator. The system showed high-speed detection of fires and blood in real-time under various conditions with low device utilization.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Telecommunications
Madyen Mohammad Saleem, Salah Abdulghani Alabady
Summary: This paper proposes an energy-efficient multipath clustering with load balancing routing protocol to prolong the network lifetime of WMSNs. The protocol segments the network into layers of clusters and uses multi-hop to transmit sensing data from the sensor to the sink. Simulation results show that the proposed protocol improves energy dissipation, network life-times, and network stability compared to existing protocols.
IET WIRELESS SENSOR SYSTEMS
(2023)
Article
Nanoscience & Nanotechnology
Muhammad Umer, Saima Sadiq, Arif Mehmood, Imran Ashraf, Gyu Sang Choi, Sadia Din
Summary: Educational data mining has gained attention in recent years for improving the online learning environment and predicting student academic performance by analyzing and mining information stored in educational systems.
INTERNATIONAL JOURNAL OF NANOTECHNOLOGY
(2023)
Article
Computer Science, Information Systems
Noor Raad Saadallah, Salah Abdulghani Alabady
Summary: This article discusses the advantages and disadvantages of clustering when combined with cutting-edge technologies in the field of IoT. It introduces the effectiveness of Hierarchical Cluster-based protocols and Hierarchical Chain-based approaches in extending the lifetime of network sensors. Additionally, this survey provides valuable insights into the field of IoT clustering studies, deepens the understanding of design issues in IoT networks, and sheds light on its potential applications in cutting-edge IoT-integrated technologies.
JORDAN JOURNAL OF ELECTRICAL ENGINEERING
(2023)
Article
Engineering, Multidisciplinary
Adedoyin A. Hussain, Fadi Al-Turjman
Summary: The internet of medical things allows patients to access flexible and virtualized devices over the internet, but task scheduling is a fundamental issue. A hybrid genetic algorithm AI method is proposed to improve task scheduling efficiency and reduce cost and time. This research can enhance the operational efficiency of the internet of medical things.
CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES
(2023)
Article
Mathematical & Computational Biology
Auwalu Saleh Mubarak, Zubaida Said Ameen, Fadi Al-Turjman
Summary: This article discusses the importance of identifying potholes on vehicles and introduces the method of developing object detection models using deep learning and computer vision techniques. The research results show that the model trained on images filtered using Gaussian smoothing performs the best.
MATHEMATICAL BIOSCIENCES AND ENGINEERING
(2023)