Ali A. Ghorbani

790 total citations · 1 hit paper
23 papers, 451 citations indexed

About

Ali A. Ghorbani is a scholar working on Computer Networks and Communications, Signal Processing and Artificial Intelligence. According to data from OpenAlex, Ali A. Ghorbani has authored 23 papers receiving a total of 451 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Computer Networks and Communications, 13 papers in Signal Processing and 13 papers in Artificial Intelligence. Recurrent topics in Ali A. Ghorbani's work include Network Security and Intrusion Detection (15 papers), Advanced Malware Detection Techniques (13 papers) and Internet Traffic Analysis and Secure E-voting (8 papers). Ali A. Ghorbani is often cited by papers focused on Network Security and Intrusion Detection (15 papers), Advanced Malware Detection Techniques (13 papers) and Internet Traffic Analysis and Secure E-voting (8 papers). Ali A. Ghorbani collaborates with scholars based in Canada, Iran and South Korea. Ali A. Ghorbani's co-authors include Sajjad Dadkhah, Arash Habibi Lashkari, Euclides Carlos Pinto Neto, Hassan Mahdikhani, Shahrear Iqbal, Pulei Xiong, Suprio Ray, Farzaneh Shoeleh, Barjinder Kaur and Philippe Lamontagne and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Sensors.

In The Last Decade

Ali A. Ghorbani

21 papers receiving 426 citations

Hit Papers

Internet of Things (IoT) security dataset evolution: Chal... 2023 2026 2024 2025 2023 25 50 75 100
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. Internet of Things (IoT) security dataset evolution: Challenges and future directions
    2023 100 citations Barjinder Kaur, Sajjad Dadkhah et al. Internet of Things profile →

Peers

Ali A. Ghorbani
Pulei Xiong Canada
Kehe Wu China
Francisco J. Aparicio‐Navarro United Kingdom
Kriti Bhushan India
Basant Subba India
Yubo Song China
İlhan Fırat Kılınçer Türkiye
Ali Alqazzaz Saudi Arabia
Giampaolo Bovenzi Italy
Pulei Xiong Canada
Ali A. Ghorbani
Citations per year, relative to Ali A. Ghorbani Ali A. Ghorbani (= 1×) peers Pulei Xiong

Countries citing papers authored by Ali A. Ghorbani

Since Specialization
Citations

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

Fields of papers citing papers by Ali A. Ghorbani

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ali A. Ghorbani. 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 Ali A. Ghorbani. The network helps show where Ali A. Ghorbani may publish in the future.

Co-authorship network of co-authors of Ali A. Ghorbani

This figure shows the co-authorship network connecting the top 25 collaborators of Ali A. Ghorbani. A scholar is included among the top collaborators of Ali A. Ghorbani 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 Ali A. Ghorbani. Ali A. Ghorbani 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.
2.
Nejati, Fatemeh, et al.. (2024). A lightweight IoT device identification using enhanced behavioral-based features. Peer-to-Peer Networking and Applications. 18(2). 3 indexed citations
3.
Kaur, Barjinder, Sajjad Dadkhah, Farzaneh Shoeleh, et al.. (2023). Internet of Things (IoT) security dataset evolution: Challenges and future directions. Internet of Things. 22. 100780–100780. 100 indexed citations breakdown →
4.
Ghorbani, Ali A., et al.. (2023). A gradient-based approach for adversarial attack on deep learning-based network intrusion detection systems. Applied Soft Computing. 137. 110173–110173. 42 indexed citations
5.
Dadkhah, Sajjad, et al.. (2022). Towards the Development of a Realistic Multidimensional IoT Profiling Dataset. 1–11. 91 indexed citations
6.
Le, Phong T., et al.. (2022). Data Breach: Analysis, Countermeasures, and Challenges. International Journal of Information and Computer Security. 1(1). 1–1. 3 indexed citations
7.
Neto, Euclides Carlos Pinto, Sajjad Dadkhah, & Ali A. Ghorbani. (2022). Sustainable and Secure Optimization of Load Distribution in Edge Computing. 40–45. 2 indexed citations
8.
Neto, Euclides Carlos Pinto, et al.. (2022). Ensemble-based Intrusion Detection for Internet of Things Devices. NPARC. 34–39. 12 indexed citations
9.
Zhang, Xichen, Songnian Zhang, Suprio Ray, & Ali A. Ghorbani. (2022). Efficient and Privacy-preserving Worker Selection in Mobile Crowdsensing Over Tentative Future Trajectories. 11. 1–8. 2 indexed citations
10.
Lashkari, Arash Habibi, et al.. (2022). The sound of intrusion: A novel network intrusion detection system. Computers & Electrical Engineering. 104. 108455–108455. 18 indexed citations
11.
Dadkhah, Sajjad, Euclides Carlos Pinto Neto, Pulei Xiong, et al.. (2022). Classification and Analysis of Adversarial Machine Learning Attacks in IoT: a Label Flipping Attack Case Study. SHILAP Revista de lepidopterología. 3–14. 6 indexed citations
12.
Dadkhah, Sajjad, Euclides Carlos Pinto Neto, Pulei Xiong, et al.. (2022). Label Noise Detection in IoT Security based on Decision Tree and Active Learning. NPARC. 46–53. 6 indexed citations
13.
Ghorbani, Ali A. & Seyed Mostafa Fakhrahmad. (2022). A Deep Learning Approach to Network Intrusion Detection Using a Proposed Supervised Sparse Auto-encoder and SVM. Iranian Journal of Science and Technology Transactions of Electrical Engineering. 46(3). 829–846. 12 indexed citations
14.
Shoeleh, Farzaneh, Sajjad Dadkhah, Barjinder Kaur, et al.. (2021). A feature exploration approach for IoT attack type classification. NPARC. 582–588. 16 indexed citations
15.
Ghorbani, Ali A., et al.. (2020). Positioning Using Classification and Regression: Case study of Oman Sea. 4(3). 35–41. 1 indexed citations
16.
Ghorbani, Ali A., et al.. (2020). Hy-Bridge: A Hybrid Blockchain for Privacy-Preserving and Trustful Energy Transactions in Internet-of-Things Platforms. Sensors. 20(3). 928–928. 29 indexed citations
17.
Kadir, Andi Fitriah Abdul, Natalia Stakhanova, & Ali A. Ghorbani. (2018). Understanding Android Financial Malware Attacks:Taxonomy, Characterization, and Challenges. Journal of Cyber Security and Mobility. 1 indexed citations
18.
Lashkari, Arash Habibi, Min Chen, & Ali A. Ghorbani. (2018). A Survey on User Profiling Model for Anomaly Detection in Cyberspace. Journal of Cyber Security and Mobility. 9 indexed citations
19.
Stakhanova, Natalia, et al.. (2008). A Behavioral Model of Ideologically-motivated “Snowball” Attacks. 30. 88–95. 2 indexed citations
20.
Ghorbani, Ali A.. (2004). Introduction to Special Issue on Agent Technologies for Electronic Business. Computational Intelligence. 20(4). 527–531.

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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