Muder Almiani

1.4k total citations · 1 hit paper
64 papers, 867 citations indexed

About

Muder Almiani is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Muder Almiani has authored 64 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Computer Networks and Communications, 27 papers in Artificial Intelligence and 25 papers in Information Systems. Recurrent topics in Muder Almiani's work include Network Security and Intrusion Detection (11 papers), IoT and Edge/Fog Computing (9 papers) and User Authentication and Security Systems (8 papers). Muder Almiani is often cited by papers focused on Network Security and Intrusion Detection (11 papers), IoT and Edge/Fog Computing (9 papers) and User Authentication and Security Systems (8 papers). Muder Almiani collaborates with scholars based in Jordan, United States and Kuwait. Muder Almiani's co-authors include Abdul Razaque, Amer Al‐Rahayfeh, Saleh Atiewi, Yaser Jararweh, Bandar Alotaibi, Munif Alotaibi, Salman Yussof, Syed A. Rizvi, Abdullah Abuhussein and Bilal Abu-Salih and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.

In The Last Decade

Muder Almiani

56 papers receiving 827 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Deep recurrent neural network for IoT intrusion detection system

2019 291 citations Muder Almiani, Amer Al‐Rahayfeh et al. Simulation Modelling Practice and Theory profile →

Peers

Muder Almiani

CNC

AI

SP

IS

EEE

Hui Lu China

Hongliang Zhu China

Shankar Karuppayah Malaysia

Zhiyang Li China

Jinoh Kim United States

Noura Limam Canada

Danh Le-Phuoc Germany

Cheqing Jin China

Li Pan China

Yang‐Sae Moon South Korea

Hui Lu China

Muder Almiani

352 ×0.7

CNC

340 ×0.8

AI

197 ×0.8

SP

181 ×0.8

IS

90 ×1.0

EEE

Citations per year, relative to Muder Almiani Muder Almiani (= 1×) peers Hui Lu

Countries citing papers authored by Muder Almiani

Since Specialization

Citations

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

Fields of papers citing papers by Muder Almiani

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muder Almiani

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Issa, Tomayess, et al.. (2025). Digital nudging model for learning management systems: Saudi Arabia perspective. Heliyon. 11(6). e42672–e42672.

2.

AlZu’bi, Shadi, Tarek Kanan, Mohammed Elbes, & Muder Almiani. (2025). A NEUROMORPHIC ANALYSIS OF CLIMATE PATTERNS FOR COMPLEX ENVIRONMENTAL FRACTAL MODELING. Fractals. 33(2).

3.

Razaque, Abdul, et al.. (2024). Blockchain-enabled heterogeneous 6G supported secure vehicular management system over cloud edge computing. Internet of Things. 25. 101115–101115. 9 indexed citations

4.

Abu-Salih, Bilal, et al.. (2024). DAO-LGBM: dual annealing optimization with light gradient boosting machine for advocates prediction in online customer engagement. Cluster Computing. 27(4). 5047–5073. 8 indexed citations

5.

Abu-Salih, Bilal, et al.. (2024). Credibility-based knowledge graph embedding for identifying social brand advocates. Frontiers in Big Data. 7. 1469819–1469819. 1 indexed citations

6.

Kanan, Tarek, et al.. (2024). Large Language Models for Knowledge Discovery in Healthcare. 183–190. 1 indexed citations

7.

Almiani, Muder, et al.. (2024). Knowledge Graph Embedding for Detecting Brand Advocates in Online Social Networks. 137–144.

8.

Atiewi, Saleh, Amer Al‐Rahayfeh, Muder Almiani, Abdullah Abuhussein, & Salman Yussof. (2023). Ethereum blockchain-based three factor authentication and multi-contract access control for secure smart home environment in 5G networks. Cluster Computing. 27(4). 4551–4568. 4 indexed citations

9.

Alweshah, Mohammed, et al.. (2022). Vehicle routing problems based on Harris Hawks optimization. Journal Of Big Data. 9(1). 15 indexed citations

10.

Razaque, Abdul, Yaser Jararweh, Bandar Alotaibi, et al.. (2021). Energy-efficient and secure mobile fog-based cloud for the Internet of Things. Future Generation Computer Systems. 127. 1–13. 36 indexed citations

11.

Almiani, Muder, et al.. (2021). DDoS detection in 5G-enabled IoT networks using deep Kalman backpropagation neural network. International Journal of Machine Learning and Cybernetics. 12(11). 3337–3349. 36 indexed citations

12.

Atiewi, Saleh, Amer Al‐Rahayfeh, Muder Almiani, et al.. (2020). Scalable and Secure Big Data IoT System Based on Multifactor Authentication and Lightweight Cryptography. IEEE Access. 8. 113498–113511. 52 indexed citations

13.

Almiani, Muder, et al.. (2019). A deep recurrent Q network towards self‐adapting distributed microservice architecture. Software Practice and Experience. 50(2). 116–135. 13 indexed citations

14.

Razaque, Abdul, et al.. (2019). State-of-art review of information diffusion models and their impact on social network vulnerabilities. Journal of King Saud University - Computer and Information Sciences. 34(1). 1275–1294. 38 indexed citations

15.

Al‐Rahayfeh, Amer, Saleh Atiewi, Abdullah Abuhussein, & Muder Almiani. (2019). Novel Approach to Task Scheduling and Load Balancing Using the Dominant Sequence Clustering and Mean Shift Clustering Algorithms. Future Internet. 11(5). 109–109. 29 indexed citations

16.

Almiani, Muder, et al.. (2019). Deep recurrent neural network for IoT intrusion detection system. Simulation Modelling Practice and Theory. 101. 102031–102031. 291 indexed citations breakdown →

17.

Almiani, Muder, et al.. (2018). Intelligent intrusion detection system using clustered self organized map. 138–144. 29 indexed citations

18.

Razaque, Abdul, et al.. (2018). Enhanced Risk Minimization Framework for Cloud Computing Environment. 18. 1–7. 3 indexed citations

19.

Almiani, Muder, et al.. (2018). Context-aware latency reduction protocol for secure encryption and decryption. International Journal of High Performance Computing and Networking. 12(3). 251–251. 1 indexed citations

20.

Almiani, Muder & Buket D. Barkana. (2015). A modified region growing based algorithm to vessel segmentation in magnetic resonance angiography. 1–7. 3 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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