Mujaheed Abdullahi

576 citations
15 papers · 351 · 1 hit paper · h-index 8

Impact in

Papers in

Mujaheed Abdullahi

14 papers receiving 331 citations

Mujaheed Abdullahi's Hit Papers

Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review 2022 · 245 citations
2450+1+2Years since publication50100150200

Peers

Mujaheed Abdullahi
Comparison fields: 5 of 41
  • Computer Networks and Communications 205
  • Information Systems 84
  • Artificial Intelligence 63
  • Signal Processing 11
  • Software 6
Replace M. A. Poltavtseva with:
M. A. Poltavtseva Russia
Shan Chen Hong Kong
E. Yu. Pavlenko Russia
R. Baskaran India
Hwankuk Kim South Korea
Max Landauer Austria
Tran Vu Pham Vietnam
Mayra Macas China
Hewijin Christine Jiau Taiwan
Xue Ouyang China
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Citations per year

Countries citing papers authored by Mujaheed Abdullahi

Since Specialization
Citations

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

Fields of papers citing papers by Mujaheed Abdullahi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Mujaheed Abdullahi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mujaheed Abdullahi Line = papers co-authored together Mujaheed Abdullahi links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
Detecting Cybersecurity Attacks in Internet of Things Using Artificial Intelligence Methods: A Systematic Literature Review
Hit paper breakdown →
2022245
2 202421
3 202413
4 202413
5 202411
6 20229
7 20229
8 20228
9 20238
10 20255
11 20254
12 20232
13 20242
14 20221
15 20250

About Mujaheed Abdullahi

Mujaheed Abdullahi is a scholar working on Computer Networks and Communications, Artificial Intelligence, Oncology, Software and Neurology, having authored 15 papers that have together received 351 indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (4 papers), Cutaneous Melanoma Detection and Management (2 papers), AI in cancer detection (2 papers), Brain Tumor Detection and Classification (1 paper), IoT and Edge/Fog Computing (1 paper), Artificial Intelligence Applications (1 paper), Digital Transformation in Industry (1 paper) and Impact of AI and Big Data on Business and Society (1 paper). The work is most often cited by research in Computer Networks and Communications (205 citations), Information Systems (84 citations), Artificial Intelligence (63 citations), Signal Processing (11 citations) and Software (6 citations). Mujaheed Abdullahi has collaborated with scholars based in Malaysia, Saudi Arabia and Nigeria. Frequent co-authors include Hitham Alhussian, Norshakirah Aziz, Said Jadid Abdulkadir, Yahia Mohamed Baashar, Ayed Said Alwadain, Luiz Fernando Capretz, Aliza Bt. Sarlan, Kamaluddeen Usman Danyaro, Aliyu Garba and Mohd Soperi Mohd Zahid. Their work appears in journals such as IEEE Access, Applied Sciences, Journal of King Saud University - Computer and Information Sciences, Neurocomputing and Electronics.

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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