JAFAR ABABNEH (Member, IEEE) received the
B.Sc. degree in telecommunication engineering,
in 1991, the M.Sc. degree in 2005, and the Ph.D.
degree in 2009. In 2009, he joined as the Head
of computer information and network systems
in information technology(IT), WISE University,
for four years. He was the Dean of the IT faculty, WISE University, for more than five years.
In March 2022, he joined the Abdul Aziz Al
Ghurair School of Advanced Computing (ASAC),
LUMINUS Technical University College (LTUC) for two years. He joined
the Cyber Security Department, Faculty of Information Technology, Zarqa
University, Jordan, in January 2024. He is an Associate Professor. He has
published many research papers, book chapters, patents, and books in international refereed journals and conferences. His research interests include
congestion and network performance, wireless and mobile networks, cybersecurity, wireless sensor networks (WSNs), artificial intelligence, data
mining and retrieving information
EDUCATION
Ph.D. Computer Information Systems (CIS)\ (Computer Network and Information security), The Arab Academy for Banking & Financial Sciences, Amman- Jordan, 2009.
Thesis: "Development of a Discrete-time DRED Based Multi-Queue Nodes Network Analytical Model".
M. Eng. Computer Engineering-Embedded Systems- excellent G.P.A, Yarmouk University, Irbid-Jordan, 2005.
Thesis: "Classified Systems Identification Numbers (security issues)"
B.Eng. Electrical Engineering-Communication, good G.P.A, Mu'tah University, Mu'tah- Jordan, 1991.
RESEARCH, TEACHING, or OTHER INTERESTS
Computer Networks and Communications, Information Systems, Surfaces and Interfaces, Computer Science Applications
A Review of 6G Conceptual Components, Ultra-Dense Networks, and Research Challenges Towards Cyber-Physical-Social Systems Hani Attar, Haitham Issa, Jafar Ababneh, Khosro Rezaee, Ayat Alrosan, Mohanad A. Deif, Ahmed A.A. Solyman International Journal of Crowd Science, 2026 Next-generation wireless network applications that combine the Internet of Things (IoT), intelligent edges, and connectivity technologies will benefit every area, including e-health and medical Internet of Things (M-IoT). The fifth generation (5G) mobile network technology cannot match the requirements of emerging mobile apps, which require extreme communication speed, network intelligence, ultra-low latency, comprehensive connectivity, and the capacity to manage diversely related usages. The sixth generation (6G) mobile network technology establishes new performance standards that the fifth generation (5G) mobile network technology could not satisfy. For incredibly immersive applications such as 3D communications and enormous virtual reality (VR)/ extended reality (XR) applications to be economically viable, 6G capabilities must be delivered at a large scale. Deploying several tiny cells to construct ultra-dense networks (UDN) is one option for tackling the extraordinary rise in capacity and coverage needs. The proposed work estimates that only the future 6G networks can deliver a high-performance connection with many connected devices, particularly in challenging situations such as diverse mobility, energetic environments, and extreme density. Accordingly, this article discusses the most current and forthcoming 6G network-compatible advancements to comprehensively review 6G mobile communication technologies in single survey research. At the outset, we thoroughly overview UDN and the 6G system's goals, motivations, requirements, architecture, and conceptual parts.
Enhancing DevOps Continuous Monitoring Phase: Hybrid Intrusion Detection and Ensemble Learning System (HIDELS) Jafar Ababneh, Esam Y. A. Al-Nsour, Ala'A Al-Shaikh, Mohammad Rasmi Al-Mousa, Ahmad Al-Zabin, Mahmoud Asassfeh, Hasan Abualese IEEE Access, 2026 Companies are excited to maintain high-quality software while reducing the costs of production. DevOps is a contemporary software development life cycle paradigm in which development and operations teams join together during all stages of software development. Nonetheless, security is inadequately integrated inside DevOps. Although there have been attempts to amalgamate security with DevOps, resulting in the emergence of DevSecOps, considerable progress is necessary. The aim of Hybrid Intrusion Detection and Ensemble Learning System (HIDELS) is to present the incorporation of intrusion detection into the continuous monitoring phase of DevOps, hence enhancing DevSecOps. The integration comprises five machine learning (ML) models and assesses the performance of each model independently. Subsequently, the models are consolidated into an ensemble learning (EL) framework to improve overall robustness and provide more stable predictive outcomes. The results of the individual models show the decision tree (DT) classifier outperforming all the remaining models in terms of accuracy, precision, recall, and f1-score, with 99.5%, 99.5%, 99.7%, and 99.6% on average. Conversely, the EL model attained an average of 99.4%, 99.6%, 99.7%, and 99.7% for accuracy, precision, recall, and F1-score, respectively, exceeding the performance of all other individual ML models.
Enhanced nonlinear equalization for OFDM systems in IoT-based intelligent transportation using CGLS algorithms Jafar Ababneh, Hani Attar, Zakaria Che Muda, Ilhami Colak, Mohanad A. Deif, Samir Bendoukha, Ahmed Solyman Eurasip Journal on Wireless Communications and Networking, 2025 The rapid development of intelligent transportation systems and the Internet of Things (IoT) has increased the need for robust and efficient wireless communication in high-mobility environments, such as vehicle-to-everything networks. Orthogonal frequency division multiplexing is widely used due to its high data rates and resistance to multipath fading. However, in fast-moving scenarios, Doppler effects cause interference between subcarriers, reducing signal quality. This paper proposes a practical nonlinear equalization framework based on the conjugate gradient least squares (CGLS) method to tackle this problem. Two advanced designs—a CGLS-based block decision feedback equalizer and a regularized least squares CGLS sliding window equalizer—are introduced and tested. Simulation results show that the proposed methods significantly reduce bit error rates and achieve up to a 5 dB performance improvement over traditional approaches, while keeping computational costs low enough for real-time IoT applications. This work supports the development of safer, more reliable, and energy-efficient communication systems for smart and sustainable transportation. These contributions align with the United Nations Sustainable Development Goals (SDGs), specifically SDG 9 (Industry, Innovation, and Infrastructure), SDG 11 (Sustainable Cities and Communities), and SDG 13 (Climate Action) by supporting the development of resilient, energy-efficient, and scalable digital communication infrastructures for smart mobility and urban sustainability.
B5G Applications and Emerging Services in Smart IoT Environments Hani Attar, Mohammed Alghanim, Jafar Ababneh, Khosro Rezaee, Ayat Alrosan, Mohanad A. Deif International Journal of Crowd Science, 2025 So far, the communication standard development requires specific parameters to achieve the requests of the desired application, most frequently, the connection speed rate. On the other hand, the term Beyond the Fifth Generation (B5G) symbolizes certain specifications required to succeed the future-proof of the Fifth Generation (5G), i.e., the predicted high-level parameters, such as ultra-reliable low-latency communications, massive machine-type communications, and improved mobile broadband, which are essential for the expected high-level future applications; consequently, 5G wireless (cellular) networks must be reconsidered precisely and in-depth to cope with the applications' required high-level standard parameters in B5G. Therefore, it is crucial to develop novel wireless access configurations and technologies that utilize additional spectrum. However, this alone is not sufficient for now. Incorporating technologies such as software-defined networking, cloud computing, machine learning, 3D networking, and network function virtualization into B5G networks is imperative due to raised concerns regarding decentralization, transparency, interoperability, privacy, and security. This page provides a comprehensive overview of B5G's design, functionality, and security, as well as its relationship to cloud computing. Furthermore, the proposed study examines the techniques employed for data transmission in B5G applications, such as Vehicle-to-Vehicle (V2V), Device-to-Device (D2D), and Machine to Machine (M2M) transmissions. Lastly, the proposed study focuses on essential technology based software services, such as healthcare, smart grid, tourism, and agricultural services. These services use the advantages of B5G communication networks and cloud computing. So, the proposed work collects all the necessary information for researches and developers in one article, supported by the most up-to-date references.
Efficient Beam Selection in mmWave Cellular Systems Using Neural Networks and K-Nearest Neighbors Based on GPS Coordinates Ababneh, Jafar, Attar, Hani, Solyman, Ahmed, Alrosan, Ayat, Agieb, Ramy Applied Mathematics and Information Sciences, 2025 With B5G moving towards 6G, the possibility of having even higher capacity and lower latency is becoming more realistic and expected to be driven more by mmWave frequencies. However, a major issue in these systems remains the downlink beam alignment and training procedure within mmWave cellular networks. Beam selection, as part of the physical layer and the medium access control sublayer, is critical for discovering and pairing superior beams for reliable connections. In this research, machine learning using neural networks (NN) and K-nearest neighbours (KNN) is proposed for selecting the beam based only on the GPS coordinates of the receiver. This method is more efficient than conventional methods that may involve, for instance, protracted or computationally expensive beam searches or hard-to-obtain side information. An improved selection is achieved by proposing a novel selection architecture in the proposed method using NN-KNN while ensuring the best performance out of competing methods by using the average received signal reference power (RSRP) and top-K accuracy metric. This approach has shown that, despite imprecise data of the receiver location, it is a more efficient solution for future wireless communications systems. The results imply potential improvements in beam selection concerning efficiency, which can support the further development of mmWave for future B5G and 6G networks.
APPLICATION OF CLOUD COMPUTING TECHNOLOGIES IN DIGITAL MARKETING MANAGEMENT OF COMPANIES Journal of Theoretical and Applied Information Technology, 2025
A Proposed Approach for Risk Planning and Management Mohammed N. Al Refai, Yazan Al-Smadi, Adai Al-Momani, Zeyad M. Jamhawi, Ahmed Ali Otoom, Issa Atoum, Ahid Yaseen, Jafar Ababneh, Mohammad Kanan 2024 25th International Arab Conference on Information Technology Acit 2024, 2024
Augmented order preserving minimal perfect hash functions for very large digital libraries Recent Researches in Communications and IT Proc of the 15th Wseas Int Conf on Communications Part of the 15th Wseas Cscc Multiconference Proc of the 5th Int Conf on CIT 11, 2011
Naive bayesian and K-nearest neighbour to categorize Arabic text data Esm 2008 2008 European Simulation and Modelling Conference Modelling and Simulation 2008, 2008