Adel Binbusayyis

1.1k total citations
40 papers, 715 citations indexed

About

Adel Binbusayyis is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Adel Binbusayyis has authored 40 papers receiving a total of 715 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 16 papers in Computer Networks and Communications and 8 papers in Information Systems. Recurrent topics in Adel Binbusayyis's work include Network Security and Intrusion Detection (10 papers), Anomaly Detection Techniques and Applications (8 papers) and IoT and Edge/Fog Computing (6 papers). Adel Binbusayyis is often cited by papers focused on Network Security and Intrusion Detection (10 papers), Anomaly Detection Techniques and Applications (8 papers) and IoT and Edge/Fog Computing (6 papers). Adel Binbusayyis collaborates with scholars based in Saudi Arabia, Pakistan and United Kingdom. Adel Binbusayyis's co-authors include Thavavel Vaiyapuri, Abdullah Alqahtani, Shtwai Alsubai, Muhammad Attique Khan, Vijayakumar Varadarajan, Haya Alaskar, Mohemmed Sha, Shuihua Wang‎, Jaehyuk Cha and Aimal Khan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Computers in Human Behavior and IEEE Access.

In The Last Decade

Adel Binbusayyis

37 papers receiving 674 citations

Peers

Adel Binbusayyis

CNC

CVPR

P. Chinnasamy India

Reem Alkanhel Saudi Arabia

Ruba Abu Khurma Jordan

Ling Gao China

P. Deepalakshmi India

Riaz Ullah Khan China

Danial Javaheri South Korea

S. Vimal India

Qingtao Wu China

Zhifeng Xiao United States

P. Chinnasamy India

Adel Binbusayyis

273 ×0.8

289 ×0.9

CNC

98 ×0.7

122 ×1.2

CVPR

314 ×3.3

Citations per year, relative to Adel Binbusayyis Adel Binbusayyis (= 1×) peers P. Chinnasamy

Countries citing papers authored by Adel Binbusayyis

Since Specialization

Citations

This map shows the geographic impact of Adel Binbusayyis's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Adel Binbusayyis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adel Binbusayyis more than expected).

Fields of papers citing papers by Adel Binbusayyis

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Adel Binbusayyis. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Adel Binbusayyis. The network helps show where Adel Binbusayyis may publish in the future.

Co-authorship network of co-authors of Adel Binbusayyis

This figure shows the co-authorship network connecting the top 25 collaborators of Adel Binbusayyis. A scholar is included among the top collaborators of Adel Binbusayyis based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Adel Binbusayyis. Adel Binbusayyis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Binbusayyis, Adel & Mohemmed Sha. (2025). Secure and privacy-preserving intrusion detection in smart networks via blockchain-based federated learning and optimized deep learning models. 100355–100355.

Binbusayyis, Adel. (2025). Innovative Defense: Deep Learning-Powered Intrusion Detection for IoT Networks. IEEE Access. 13. 31105–31120. 1 indexed citations

Binbusayyis, Adel & Mohemmed Sha. (2024). Stability Prediction in Smart Grid Using PSO Optimized XGBoost Algorithm with Dynamic Inertia Weight Updation. Computer Modeling in Engineering & Sciences. 142(1). 909–931. 4 indexed citations

Binbusayyis, Adel & Mohemmed Sha. (2024). Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism. Heliyon. 11(1). e41507–e41507. 6 indexed citations

Vaiyapuri, Thavavel & Adel Binbusayyis. (2023). Deep self-taught learning framework for intrusion detection in cloud computing environment. IAES International Journal of Artificial Intelligence. 13(1). 747–747. 3 indexed citations

Attıa, Abdelouahab, et al.. (2023). An Archive-Guided Equilibrium Optimizer Based on Epsilon Dominance for Multi-Objective Optimization Problems. Mathematics. 11(12). 2680–2680. 4 indexed citations

Alqahtani, Abdullah, Shtwai Alsubai, Adel Binbusayyis, et al.. (2023). Optimizing Kidney Stone Prediction through Urinary Analysis with Improved Binary Particle Swarm Optimization and eXtreme Gradient Boosting. Mathematics. 11(7). 1717–1717. 6 indexed citations

Alsubai, Shtwai, Abdullah Alqahtani, Adel Binbusayyis, et al.. (2023). Quantum Computing Meets Deep Learning: A Promising Approach for Diabetic Retinopathy Classification. Mathematics. 11(9). 2008–2008. 13 indexed citations

Alsubai, Shtwai, Abdullah Alqahtani, Adel Binbusayyis, et al.. (2023). A Quantum Computing-Based Accelerated Model for Image Classification Using a Parallel Pipeline Encoded Inception Module. Mathematics. 11(11). 2513–2513. 3 indexed citations

10.

Alqahtani, Abdullah, Shtwai Alsubai, Adel Binbusayyis, et al.. (2023). Prediction of Urinary Tract Infection in IoT-Fog Environment for Smart Toilets Using Modified Attention-Based ANN and Machine Learning Algorithms. Applied Sciences. 13(10). 5860–5860. 6 indexed citations

11.

Hafiz, Abdul Mueed, M. Hassaballah, & Adel Binbusayyis. (2023). Formula-Driven Supervised Learning in Computer Vision: A Literature Survey. Applied Sciences. 13(2). 723–723. 7 indexed citations

12.

Binbusayyis, Adel, et al.. (2022). An investigation and comparison of machine learning approaches for intrusion detection in IoMT network. The Journal of Supercomputing. 78(15). 17403–17422. 51 indexed citations

13.

Hamza, Ameer, Muhammad Attique Khan, Shuihua Wang‎, et al.. (2022). COVID-19 classification using chest X-ray images: A framework of CNN-LSTM and improved max value moth flame optimization. Frontiers in Public Health. 10. 948205–948205. 28 indexed citations

14.

Khan, Muhammad Attique, Abdullah Alqahtani, Aimal Khan, et al.. (2022). Cucumber Leaf Diseases Recognition Using Multi Level Deep Entropy-ELM Feature Selection. Applied Sciences. 12(2). 593–593. 56 indexed citations

15.

Khan, Muhammad Attique, et al.. (2022). COVID-19 Classification from Chest X-Ray Images: A Framework of Deep Explainable Artificial Intelligence. Computational Intelligence and Neuroscience. 2022. 1–14. 33 indexed citations

16.

Rubab, Saddaf, Muhammad Attique Khan, Rizwan Ali Naqvi, et al.. (2022). Driver’s emotion and behavior classification system based on Internet of Things and deep learning for Advanced Driver Assistance System (ADAS). Computer Communications. 194. 258–267. 15 indexed citations

17.

Khurshid, Khawar, et al.. (2022). ILS Validity Analysis for Secondary Grade through Factor Analysis and Internal Consistency Reliability. Sustainability. 14(13). 7950–7950. 1 indexed citations

18.

Iqbal, Zeshan, et al.. (2022). An ANN based bidding strategy for resource allocation in cloud computing using IoT double auction algorithm. Sustainable Energy Technologies and Assessments. 52. 102358–102358. 4 indexed citations

19.

Binbusayyis, Adel & Thavavel Vaiyapuri. (2020). Comprehensive analysis and recommendation of feature evaluation measures for intrusion detection. Heliyon. 6(7). e04262–e04262. 26 indexed citations

20.

Vaiyapuri, Thavavel & Adel Binbusayyis. (2020). Application of deep autoencoder as an one-class classifier for unsupervised network intrusion detection: a comparative evaluation. PeerJ Computer Science. 6. e327–e327. 32 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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