Chin‐Wei Tien

493 total citations
20 papers, 322 citations indexed

About

Chin‐Wei Tien is a scholar working on Signal Processing, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Chin‐Wei Tien has authored 20 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Signal Processing, 14 papers in Artificial Intelligence and 9 papers in Computer Networks and Communications. Recurrent topics in Chin‐Wei Tien's work include Advanced Malware Detection Techniques (14 papers), Network Security and Intrusion Detection (9 papers) and Digital and Cyber Forensics (5 papers). Chin‐Wei Tien is often cited by papers focused on Advanced Malware Detection Techniques (14 papers), Network Security and Intrusion Detection (9 papers) and Digital and Cyber Forensics (5 papers). Chin‐Wei Tien collaborates with scholars based in Taiwan and Japan. Chin‐Wei Tien's co-authors include Sy‐Yen Kuo, Jianwei Liao, Jenq‐Haur Wang, Shang-Wen Chen, Tao Ban, Hsing-Kuo Pao, Hahn-Ming Lee, Albert B. Jeng, Te-En Wei and Ing-Yi Chen and has published in prestigious journals such as Computers, Cybersecurity and IEEE Embedded Systems Letters.

In The Last Decade

Chin‐Wei Tien

18 papers receiving 301 citations

Peers

Chin‐Wei Tien
Faheem Ullah Australia
Nora Cuppens-Boulahia France
Phan The Duy Vietnam
Aaron Zimba China
Katharina Hofer-Schmitz Austria
John Douglas Howard United States
Cataldo Basile Italy
Gbadebo Ayoade United States
Anton V. Uzunov Australia
Erkuden Rios Spain
Faheem Ullah Australia
Chin‐Wei Tien
Citations per year, relative to Chin‐Wei Tien Chin‐Wei Tien (= 1×) peers Faheem Ullah

Countries citing papers authored by Chin‐Wei Tien

Since Specialization
Citations

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

Fields of papers citing papers by Chin‐Wei Tien

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Chin‐Wei Tien. 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 Chin‐Wei Tien. The network helps show where Chin‐Wei Tien may publish in the future.

Co-authorship network of co-authors of Chin‐Wei Tien

This figure shows the co-authorship network connecting the top 25 collaborators of Chin‐Wei Tien. A scholar is included among the top collaborators of Chin‐Wei Tien 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 Chin‐Wei Tien. Chin‐Wei Tien 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.
Tien, Chin‐Wei, et al.. (2023). Hardware Trojan Detection Method Against Balanced Controllability Trigger Design. IEEE Embedded Systems Letters. 16(2). 178–181. 1 indexed citations
2.
Chen, Chih‐Wei, et al.. (2022). Semi-supervised Trojan Nets Classification Using Anomaly Detection Based on SCOAP Features. 2022 IEEE International Symposium on Circuits and Systems (ISCAS). 2423–2427. 2 indexed citations
3.
4.
Tien, Chin‐Wei, et al.. (2021). ICPFuzzer: proprietary communication protocol fuzzing by using machine learning and feedback strategies. Cybersecurity. 4(1). 7 indexed citations
5.
Chen, Shang-Wen, et al.. (2021). An Experience in Enhancing Machine Learning Classifier Against Low-Entropy Packed Malwares. 77–86. 1 indexed citations
6.
Tien, Chin‐Wei, et al.. (2021). Using Autoencoders for Anomaly Detection and Transfer Learning in IoT. Computers. 10(7). 88–88. 39 indexed citations
7.
Tien, Chin‐Wei, et al.. (2020). Evaluating Robustness of AI Models against Adversarial Attacks. 47–54. 16 indexed citations
8.
9.
Tien, Chin‐Wei, Shang-Wen Chen, Tao Ban, & Sy‐Yen Kuo. (2020). Machine Learning Framework to Analyze IoT Malware Using ELF and Opcode Features. 1(1). 1–19. 40 indexed citations
10.
Tien, Chin‐Wei, et al.. (2019). KubAnomaly: Anomaly detection for the Docker orchestration platform with neural network approaches. Engineering Reports. 1(5). 39 indexed citations
11.
Liao, Jianwei, et al.. (2019). SoliAudit: Smart Contract Vulnerability Assessment Based on Machine Learning and Fuzz Testing. 458–465. 90 indexed citations
12.
Chao, Wei‐Chieh, et al.. (2018). Design and Implement Binary Fuzzing Based on Libfuzzer. 1–2.
13.
Tien, Chin‐Wei, et al.. (2018). UFO - Hidden Backdoor Discovery and Security Verification in IoT Device Firmware. 18–23. 12 indexed citations
14.
Tien, Chin‐Wei, et al.. (2017). Memory forensics using virtual machine introspection for Malware analysis. 21 indexed citations
15.
Tien, Chin‐Wei, et al.. (2015). Efficient spear-phishing threat detection using hypervisor monitor. 299–303. 8 indexed citations
16.
Wei, Te-En, et al.. (2012). Android privacy. 13 indexed citations
17.
Wei, Te-En, et al.. (2012). Android privacy. 1830–1837. 6 indexed citations
18.
Tien, Chin‐Wei, et al.. (2012). Efficient and effective NIDS for cloud virtualization environment. 249–254. 14 indexed citations
19.
Wei, Te-En, et al.. (2011). RePEF — A system for Restoring Packed Executable File for malware analysis. 519–527. 2 indexed citations
20.
Tien, Chin‐Wei, et al.. (2011). AOS: An optimized sandbox method used in behavior-based malware detection. 5137. 404–409. 5 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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2026