Mee Lan Han

538 total citations
13 papers, 323 citations indexed

About

Mee Lan Han is a scholar working on Artificial Intelligence, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Mee Lan Han has authored 13 papers receiving a total of 323 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Artificial Intelligence, 6 papers in Computer Networks and Communications and 5 papers in Electrical and Electronic Engineering. Recurrent topics in Mee Lan Han's work include Anomaly Detection Techniques and Applications (6 papers), Network Security and Intrusion Detection (6 papers) and Vehicular Ad Hoc Networks (VANETs) (5 papers). Mee Lan Han is often cited by papers focused on Anomaly Detection Techniques and Applications (6 papers), Network Security and Intrusion Detection (6 papers) and Vehicular Ad Hoc Networks (VANETs) (5 papers). Mee Lan Han collaborates with scholars based in South Korea and United States. Mee Lan Han's co-authors include Huy Kang Kim, Byung Il Kwak, Seong Hoon Jeong, Aziz Mohaisen, Sangjin Lee, Jungheum Park, Ah Reum Kang and Jung Kyu Park and has published in prestigious journals such as IEEE Transactions on Power Systems, Expert Systems with Applications and IEEE Access.

In The Last Decade

Mee Lan Han

12 papers receiving 311 citations

Peers

Mee Lan Han
Tuan Vuong United Kingdom
Mahdi Dibaei Australia
Shahab Tayeb United States
Anatolij Bezemskij United Kingdom
Mee Lan Han
Citations per year, relative to Mee Lan Han Mee Lan Han (= 1×) peers Rens W. van der Heijden

Countries citing papers authored by Mee Lan Han

Since Specialization
Citations

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

Fields of papers citing papers by Mee Lan Han

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mee Lan Han. 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 Mee Lan Han. The network helps show where Mee Lan Han may publish in the future.

Co-authorship network of co-authors of Mee Lan Han

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

All Works

13 of 13 papers shown
1.
Han, Mee Lan, et al.. (2024). ECo-Bag: An elastic container based on merkle tree as a universal digital evidence bag. Forensic Science International Digital Investigation. 49. 301725–301725. 2 indexed citations
2.
Jeong, Seong Hoon, Huy Kang Kim, Mee Lan Han, & Byung Il Kwak. (2023). AERO: Automotive Ethernet Real-Time Observer for Anomaly Detection in In-Vehicle Networks. IEEE Transactions on Industrial Informatics. 20(3). 4651–4662. 11 indexed citations
3.
Han, Mee Lan, Byung Il Kwak, & Huy Kang Kim. (2022). TOW-IDS: Intrusion Detection System Based on Three Overlapped Wavelets for Automotive Ethernet. IEEE Transactions on Information Forensics and Security. 18. 411–422. 26 indexed citations
4.
Kwak, Byung Il, et al.. (2022). Intrusion Detection and Identification Using Tree-Based Machine Learning Algorithms on DCS Network in the Oil Refinery. IEEE Transactions on Power Systems. 37(6). 4673–4682. 14 indexed citations
5.
Han, Mee Lan, Byung Il Kwak, & Huy Kang Kim. (2022). Cheating and Detection Method in Massively Multiplayer Online Role-Playing Game: Systematic Literature Review. IEEE Access. 10. 49050–49063. 9 indexed citations
6.
Han, Mee Lan, Byung Il Kwak, & Huy Kang Kim. (2021). Event-Triggered Interval-Based Anomaly Detection and Attack Identification Methods for an In-Vehicle Network. IEEE Transactions on Information Forensics and Security. 16. 2941–2956. 48 indexed citations
7.
Kwak, Byung Il, Mee Lan Han, & Huy Kang Kim. (2020). Driver Identification Based on Wavelet Transform Using Driving Patterns. IEEE Transactions on Industrial Informatics. 17(4). 2400–2410. 36 indexed citations
8.
Kwak, Byung Il, Mee Lan Han, & Huy Kang Kim. (2020). Cosine similarity based anomaly detection methodology for the CAN bus. Expert Systems with Applications. 166. 114066–114066. 40 indexed citations
9.
Han, Mee Lan, Byung Il Kwak, & Huy Kang Kim. (2019). CBR-Based Decision Support Methodology for Cybercrime Investigation: Focused on the Data-Driven Website Defacement Analysis. Security and Communication Networks. 2019. 1–21. 10 indexed citations
10.
Han, Mee Lan, Byung Il Kwak, & Huy Kang Kim. (2018). Anomaly intrusion detection method for vehicular networks based on survival analysis. Vehicular Communications. 14. 52–63. 118 indexed citations
11.
Han, Mee Lan, et al.. (2016). WHAP: Web-hacking profiling using Case-Based Reasoning. 344–345. 6 indexed citations
12.
Park, Jung Kyu, Mee Lan Han, & Huy Kang Kim. (2015). A Study of Cheater Detection in FPS Game by using User Log Analysis. Journal of Korea Game Society. 15(3). 177–187. 1 indexed citations
13.
Han, Mee Lan, et al.. (2013). Applying CBR algorithm for cyber infringement profiling system. Journal of the Korea Institute of Information Security and Cryptology. 23(6). 1069–1086. 2 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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