Nate Mathews
Impact in
- Artificial Intelligence top 5%
- Internet Traffic Analysis and Secure E-voting
- Hate Speech and Cyberbullying Detection
- Adversarial Robustness in Machine Learning
- Privacy-Preserving Technologies in Data
- Signal Processing top 10%
- Advanced Malware Detection Techniques
Papers in
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- Internet Traffic Analysis and Secure E-voting 10
- Hate Speech and Cyberbullying Detection 6
- Privacy-Preserving Technologies in Data 2
- Adversarial Robustness in Machine Learning 1
- Authorship Attribution and Profiling 1
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- Network Security and Intrusion Detection 4
- Co-authors
- Matthew Wright (11 shared papers)Mohammad Saidur Rahman (6 shared papers)Payap Sirinam (2 shared papers)Nicholas Hopper (4 shared papers)James K Holland (3 shared papers)Mohsen Imani (1 shared paper)
- Journals
- IEEE Transactions on Information Forensics and Security (1 paper)Proceedings on Privacy Enhancing Technologies (1 paper)arXiv (Cornell University) (1 paper)
- Partner nations
- United StatesSouth KoreaThailand
In The Last Decade
Nate Mathews
12 papers receiving 232 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 231
- Signal Processing 62
- Computer Networks and Communications 131
- Computer Vision and Pattern Recognition 59
- Information Systems 60
Countries citing papers authored by Nate Mathews
This map shows the geographic impact of Nate Mathews'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 Nate Mathews with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nate Mathews more than expected).
Fields of papers citing papers by Nate Mathews
This network shows the impact of papers produced by Nate Mathews. 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 Nate Mathews. The network helps show where Nate Mathews may publish in the future.
Co-authors
The 6 scholars most cited alongside Nate Mathews, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 147 | |
| 2 | 2021 | 34 | |
| 3 | 2023 | 27 | |
| 4 | 2022 | 18 | |
| 5 | 2018 | 5 | |
| 6 | 2024 | 3 | |
| 7 | 2021 | 3 | |
| 8 | Adv-DWF: Defending Against Deep-Learning-Based Website Fingerprinting Attacks with Adversarial Traces. | 2019 | 2 |
| 9 | 2024 | 1 | |
| 10 | 2025 | 1 | |
| 11 | 2019 | 1 | |
| 12 | 2024 | 1 |
About Nate Mathews
Nate Mathews is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Signal Processing, having authored 12 papers that have together received 243 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (10 papers), Hate Speech and Cyberbullying Detection (6 papers), Network Security and Intrusion Detection (4 papers), Privacy-Preserving Technologies in Data (2 papers), User Authentication and Security Systems (2 papers), Spam and Phishing Detection (1 paper), Adversarial Robustness in Machine Learning (1 paper) and Authorship Attribution and Profiling (1 paper). The work is most often cited by research in Artificial Intelligence (231 citations), Signal Processing (62 citations), Computer Networks and Communications (131 citations), Computer Vision and Pattern Recognition (59 citations) and Information Systems (60 citations). Nate Mathews has collaborated with scholars based in United States, South Korea and Thailand. Frequent co-authors include Matthew Wright, Mohammad Saidur Rahman, Payap Sirinam, Nicholas Hopper, James K Holland and Mohsen Imani. Their work appears in journals such as IEEE Transactions on Information Forensics and Security, Proceedings on Privacy Enhancing Technologies and arXiv (Cornell University).
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.