Mohammed Aljebreen

614 total citations
32 papers, 316 citations indexed

About

Mohammed Aljebreen is a scholar working on Artificial Intelligence, Computer Networks and Communications and Information Systems. According to data from OpenAlex, Mohammed Aljebreen has authored 32 papers receiving a total of 316 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 9 papers in Information Systems. Recurrent topics in Mohammed Aljebreen's work include Network Security and Intrusion Detection (12 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Malware Detection Techniques (6 papers). Mohammed Aljebreen is often cited by papers focused on Network Security and Intrusion Detection (12 papers), Sentiment Analysis and Opinion Mining (7 papers) and Advanced Malware Detection Techniques (6 papers). Mohammed Aljebreen collaborates with scholars based in Saudi Arabia, Egypt and India. Mohammed Aljebreen's co-authors include Karzan Wakil, Salil Bharany, Mashael Maashi, Sumit Badotra, Sarvesh Tanwar, Neelam Gupta, Abidemi Emmanuel Adeniyi, Mohamed K. Nour, Akashdeep Bhardwaj and Manal Abdullah Alohali and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Mohammed Aljebreen

30 papers receiving 300 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mohammed Aljebreen Saudi Arabia 9 109 99 75 74 30 32 316
Salam Al-E’mari Jordan 8 65 0.6× 243 2.5× 115 1.5× 37 0.5× 53 1.8× 30 391
Mukta Goyal India 8 181 1.7× 72 0.7× 70 0.9× 34 0.5× 15 0.5× 39 386
Ladislav Huraj Slovakia 10 126 1.2× 61 0.6× 63 0.8× 14 0.2× 18 0.6× 37 243
Christophe Gravier France 10 69 0.6× 83 0.8× 64 0.9× 21 0.3× 42 1.4× 45 360
Fatima Rayan Awad Ahmed Saudi Arabia 8 47 0.4× 49 0.5× 40 0.5× 24 0.3× 27 0.9× 15 189
Chu-Sing Yang Taiwan 10 168 1.5× 41 0.4× 106 1.4× 34 0.5× 16 0.5× 33 288
Michele Scalera Italy 12 88 0.8× 81 0.8× 82 1.1× 13 0.2× 18 0.6× 26 282
Saumay Pushp South Korea 7 137 1.3× 101 1.0× 71 0.9× 21 0.3× 92 3.1× 16 316
Manghui Tu United States 9 156 1.4× 52 0.5× 209 2.8× 29 0.4× 13 0.4× 37 388
Giti Javidi United States 7 38 0.3× 39 0.4× 42 0.6× 20 0.3× 15 0.5× 45 188

Countries citing papers authored by Mohammed Aljebreen

Since Specialization
Citations

This map shows the geographic impact of Mohammed Aljebreen'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 Mohammed Aljebreen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Aljebreen more than expected).

Fields of papers citing papers by Mohammed Aljebreen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammed Aljebreen. 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 Mohammed Aljebreen. The network helps show where Mohammed Aljebreen may publish in the future.

Co-authorship network of co-authors of Mohammed Aljebreen

This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Aljebreen. A scholar is included among the top collaborators of Mohammed Aljebreen 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 Mohammed Aljebreen. Mohammed Aljebreen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Alohali, Manal Abdullah, et al.. (2025). Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms. Scientific Reports. 15(1). 20615–20615. 1 indexed citations
2.
Alotaibi, Sultan, et al.. (2024). Explainable artificial intelligence in web phishing classification on secure IoT with cloud-based cyber-physical systems. Alexandria Engineering Journal. 110. 490–505. 8 indexed citations
3.
Aljebreen, Mohammed, et al.. (2024). Hybrid Sine-Cosine Chimp optimization based feature selection with deep learning model for threat detection in IoT sensor networks. Alexandria Engineering Journal. 102. 169–178. 8 indexed citations
4.
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6.
Alohali, Manal Abdullah, et al.. (2024). Sandpiper optimization with hybrid deep learning model for blockchain-assisted intrusion detection in iot environment. Alexandria Engineering Journal. 112. 49–62. 4 indexed citations
7.
Nour, Mohamed K., Hassan A. Alshamrani, Mesfer Al Duhayyim, et al.. (2023). Gender Identification Using Marginalised Stacked Denoising Autoencoders on Twitter Data. Intelligent Automation & Soft Computing. 36(3). 2529–2544. 1 indexed citations
8.
Duhayyim, Mesfer Al, Jaber S. Alzahrani, Abdullah Mohamed, et al.. (2023). Multi-Versus Optimization with Deep Reinforcement Learning Enabled Affect Analysis on Arabic Corpus. Computer Systems Science and Engineering. 47(3). 3049–3065. 1 indexed citations
9.
Duhayyim, Mesfer Al, et al.. (2023). Modified Sine Cosine Optimization with Adaptive Deep Belief Network for Movie Review Classification. Intelligent Automation & Soft Computing. 37(1). 283–300. 1 indexed citations
10.
Aljebreen, Mohammed, et al.. (2023). Enhancing Traffic Flow Prediction in Intelligent Cyber-Physical Systems: A Novel Bi-LSTM-Based Approach With Kalman Filter Integration. IEEE Transactions on Consumer Electronics. 70(1). 1889–1902. 10 indexed citations
11.
Aljebreen, Mohammed, et al.. (2023). Hybrid Muddy Soil Fish Optimization-Based Energy Aware Routing in IoT-Assisted Wireless Sensor Networks. Sustainability. 15(10). 8273–8273. 8 indexed citations
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13.
Aljebreen, Mohammed, et al.. (2023). Multi-Objective Seagull Optimization Algorithm with Deep Learning-Enabled Vulnerability Detection for Secure Cloud Environments. Sensors. 23(23). 9383–9383. 3 indexed citations
14.
Alohali, Manal Abdullah, Mohammed Aljebreen, Mahmoud Othman, et al.. (2023). Blockchain-Driven Image Encryption Process with Arithmetic Optimization Algorithm for Security in Emerging Virtual Environments. Sustainability. 15(6). 5133–5133. 8 indexed citations
15.
Nour, Mohamed K., Abdullah Mohamed, Abdelwahed Motwakel, et al.. (2023). Political Optimizer with Probabilistic Neural Network-Based Arabic Comparative Opinion Mining. Intelligent Automation & Soft Computing. 36(3). 3121–3137. 1 indexed citations
16.
Aljebreen, Mohammed, et al.. (2023). Exploiting Remote Sensing Imagery for Vehicle Detection and Classification Using an Artificial Intelligence Technique. Remote Sensing. 15(18). 4600–4600. 1 indexed citations
17.
Aljebreen, Mohammed, et al.. (2023). Binary Chimp Optimization Algorithm with ML Based Intrusion Detection for Secure IoT-Assisted Wireless Sensor Networks. Sensors. 23(8). 4073–4073. 16 indexed citations
18.
Duhayyim, Mesfer Al, et al.. (2023). Optimal Deep Hybrid Boltzmann Machine Based Arabic Corpus Classification Model. Computer Systems Science and Engineering. 46(3). 2755–2772.
19.
Alharbi, Abdullah, et al.. (2022). A Normalized Slicing-assigned Virtualization Method for 6G-based Wireless Communication Systems. ACM Transactions on Multimedia Computing Communications and Applications. 18(3s). 1–18. 3 indexed citations
20.
Bhardwaj, Akashdeep, Keshav Kaushik, Mashael Maashi, Mohammed Aljebreen, & Salil Bharany. (2022). Alternate Data Stream Attack Framework to Perform Stealth Attacks on Active Directory Hosts. Sustainability. 14(19). 12288–12288. 4 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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