Naeem Syed

1.6k total citations · 1 hit paper
26 papers, 1.0k citations indexed

About

Naeem Syed is a scholar working on Computer Networks and Communications, Artificial Intelligence and Information Systems. According to data from OpenAlex, Naeem Syed has authored 26 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 14 papers in Artificial Intelligence and 11 papers in Information Systems. Recurrent topics in Naeem Syed's work include Network Security and Intrusion Detection (14 papers), Advanced Malware Detection Techniques (11 papers) and Anomaly Detection Techniques and Applications (8 papers). Naeem Syed is often cited by papers focused on Network Security and Intrusion Detection (14 papers), Advanced Malware Detection Techniques (11 papers) and Anomaly Detection Techniques and Applications (8 papers). Naeem Syed collaborates with scholars based in Australia, Saudi Arabia and United States. Naeem Syed's co-authors include Zubair Baig, Mengmeng Ge, Xiping Fu, Antonio Robles‐Kelly, Ahmed Ibrahim, Craig Valli, Robin Doss, Syed Wajid Ali Shah, Adnan Anwar and Arash Shaghaghi and has published in prestigious journals such as IEEE Access, ACM Computing Surveys and Australasian Journal of Paramedicine.

In The Last Decade

Naeem Syed

24 papers receiving 984 citations

Hit Papers

Zero Trust Architecture (ZTA): A Comprehensive Survey 2022 2026 2023 2024 2022 40 80 120
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.

  1. Zero Trust Architecture (ZTA): A Comprehensive Survey
    2022 142 citations Naeem Syed, Syed Wajid Ali Shah et al. IEEE Access profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Naeem Syed Australia 11 768 527 423 293 136 26 1.0k
Abebe Diro Australia 10 954 1.2× 677 1.3× 481 1.1× 303 1.0× 138 1.0× 18 1.3k
Bruno Bogaz Zarpel�ão Brazil 13 987 1.3× 641 1.2× 523 1.2× 244 0.8× 138 1.0× 55 1.2k
Johari Abdullah Malaysia 15 919 1.2× 672 1.3× 501 1.2× 356 1.2× 78 0.6× 38 1.3k
Muna Al-Hawawreh Australia 18 747 1.0× 551 1.0× 440 1.0× 256 0.9× 194 1.4× 37 1.1k
Ameer Al-Nemrat United Kingdom 9 1.1k 1.5× 941 1.8× 683 1.6× 245 0.8× 96 0.7× 24 1.4k
Ibrahim Ghafir United Kingdom 17 851 1.1× 425 0.8× 524 1.2× 548 1.9× 99 0.7× 60 1.2k
Elena Sitnikova Australia 14 787 1.0× 568 1.1× 501 1.2× 312 1.1× 243 1.8× 53 1.1k
Divyansh Jain India 4 650 0.8× 254 0.5× 285 0.7× 388 1.3× 62 0.5× 12 945
Noshina Tariq Pakistan 18 640 0.8× 264 0.5× 156 0.4× 424 1.4× 112 0.8× 44 941
Fadele Ayotunde Alaba Nigeria 5 626 0.8× 208 0.4× 211 0.5× 365 1.2× 76 0.6× 9 867

Countries citing papers authored by Naeem Syed

Since Specialization
Citations

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

Fields of papers citing papers by Naeem Syed

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Naeem Syed

This figure shows the co-authorship network connecting the top 25 collaborators of Naeem Syed. A scholar is included among the top collaborators of Naeem Syed 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 Naeem Syed. Naeem Syed 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.
Baig, Zubair, et al.. (2025). Digital Forensics and Jurisdictional Challenges for the Industrial Internet of Things. IEEE Security & Privacy. 23(3). 40–50.
2.
Baig, Zubair, et al.. (2025). Robust and lightweighted mutual authentication scheme for drone swarm networks. Journal of Network and Computer Applications. 242. 104264–104264. 1 indexed citations
3.
Syed, Naeem, Adnan Anwar, Zubair Baig, & Sherali Zeadally. (2025). Artificial Intelligence as a Service (AIaaS) for Cloud, Fog and the Edge: State-of-the-Art Practices. ACM Computing Surveys. 57(8). 1–36. 5 indexed citations
4.
Syed, Naeem, et al.. (2024). The Role of Rule Mining in Generating Synthetic Cyber-Physical System Attack Samples. IEEE Internet of Things Magazine. 7(6). 14–19. 1 indexed citations
5.
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7.
Syed, Naeem, et al.. (2023). Fog-cloud based intrusion detection system using Recurrent Neural Networks and feature selection for IoT networks. Computer Networks. 225. 109662–109662. 50 indexed citations
8.
Syed, Naeem, Syed Wajid Ali Shah, Arash Shaghaghi, et al.. (2022). Zero Trust Architecture (ZTA): A Comprehensive Survey. IEEE Access. 10. 57143–57179. 142 indexed citations breakdown →
9.
Syed, Naeem, et al.. (2022). Securing the Smart City Airspace: Drone Cyber Attack Detection through Machine Learning. Future Internet. 14(7). 205–205. 33 indexed citations
10.
Syed, Naeem, et al.. (2022). Unsupervised Machine Learning for Drone Forensics through Flight Path Analysis. 1–6. 2 indexed citations
11.
Shah, Syed Wajid Ali, et al.. (2021). LCDA: Lightweight Continuous Device-to-Device Authentication for a Zero Trust Architecture (ZTA). Computers & Security. 108. 102351–102351. 42 indexed citations
12.
Ge, Mengmeng, Naeem Syed, Xiping Fu, Zubair Baig, & Antonio Robles‐Kelly. (2021). Towards a deep learning-driven intrusion detection approach for Internet of Things. Computer Networks. 186. 107784–107784. 140 indexed citations
13.
Syed, Naeem. (2020). IoT-MQTT based denial of service attack modelling and detection. Australasian Journal of Paramedicine. 3 indexed citations
14.
Ge, Mengmeng, et al.. (2019). Deep Learning-Based Intrusion Detection for IoT Networks. Australasian Journal of Paramedicine. 256–265. 163 indexed citations
15.
Baig, Zubair, Surasak Sanguanpong, Naeem Syed, et al.. (2019). Averaged dependence estimators for DoS attack detection in IoT networks. Future Generation Computer Systems. 102. 198–209. 83 indexed citations
16.
Hannay, Peter, et al.. (2018). XMPP architecture and security challenges in an IoT ecosystem. Australasian Journal of Paramedicine. 6 indexed citations
17.
Baig, Zubair, Patryk Szewczyk, Craig Valli, et al.. (2017). Future challenges for smart cities: Cyber-security and digital forensics. Digital Investigation. 22. 3–13. 158 indexed citations
18.
Syed, Naeem, Zubair Baig, Craig Valli, & Ahmed Ibrahim. (2017). Modelling and Evaluation of Malicious Attacks against the IoT MQTT Protocol. Australasian Journal of Paramedicine. 748–755. 59 indexed citations
19.
Sqalli, Mohammed H., et al.. (2012). Classifying malicious activities in Honeynets using entropy and volume‐based thresholds. Security and Communication Networks. 6(5). 567–583. 3 indexed citations
20.
Sqalli, Mohammed H., et al.. (2011). Identifying network traffic features suitable for honeynet data analysis. 1044–1048.

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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