Matthew Bernhard
Impact in
- Signal Processing top 1%
- Advanced Malware Detection Techniques
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- Network Security and Intrusion Detection
- IoT and Edge/Fog Computing
Papers in
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- Internet Traffic Analysis and Secure E-voting 6
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- Blockchain Technology Applications and Security 2
- User Authentication and Security Systems 2
- Spam and Phishing Detection 1
- Co-authors
- J. Alex Halderman (5 shared papers)Zakir Durumeric (2 shared papers)Michael Bailey (2 shared papers)Nick Sullivan (1 shared paper)Elie Bursztein (1 shared paper)Luca Invernizzi (1 shared paper)Joshua Mason (1 shared paper)Yi Zhou (1 shared paper)
- Journals
- Spine (1 paper)Lecture notes in computer science (2 papers)Deep Blue (University of Michigan) (1 paper)USENIX Security Symposium (1 paper)
- Partner nations
- United StatesItalyAustralia
In The Last Decade
Matthew Bernhard
10 papers receiving 863 citations
Matthew Bernhard's Hit Papers
Peers
Comparison fields: 5 of 57
- Signal Processing 487
- Computer Networks and Communications 666
- Artificial Intelligence 501
- Information Systems 250
- Hardware and Architecture 39
Countries citing papers authored by Matthew Bernhard
This map shows the geographic impact of Matthew Bernhard'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 Matthew Bernhard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Bernhard more than expected).
Fields of papers citing papers by Matthew Bernhard
This network shows the impact of papers produced by Matthew Bernhard. 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 Matthew Bernhard. The network helps show where Matthew Bernhard may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew Bernhard, 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 | Understanding the mirai botnet Hit paper breakdown → | 2017 | 747 |
| 2 | 2016 | 51 | |
| 3 | 2020 | 30 | |
| 4 | 1998 | 20 | |
| 5 | 2018 | 15 | |
| 6 | 2020 | 12 | |
| 7 | 2021 | 8 | |
| 8 | 2019 | 6 | |
| 9 | 2020 | 5 | |
| 10 | Election Security Is Harder Than You Think | 2020 | 1 |
About Matthew Bernhard
Matthew Bernhard is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Sociology and Political Science and Signal Processing, having authored 10 papers that have together received 895 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (6 papers), Blockchain Technology Applications and Security (2 papers), Advanced Malware Detection Techniques (2 papers), User Authentication and Security Systems (2 papers), Network Security and Intrusion Detection (2 papers), Spam and Phishing Detection (1 paper), Green IT and Sustainability (1 paper) and Surgical site infection prevention (1 paper). The work is most often cited by research in Signal Processing (487 citations), Computer Networks and Communications (666 citations), Artificial Intelligence (501 citations), Information Systems (250 citations) and Hardware and Architecture (39 citations). Matthew Bernhard has collaborated with scholars based in United States, Italy and Australia. Frequent co-authors include J. Alex Halderman, Zakir Durumeric, Michael Bailey, Nick Sullivan, Elie Bursztein, Luca Invernizzi, Joshua Mason, Yi Zhou, Kurt Thomas and Michalis Kallitsis. Their work appears in journals such as Spine, Lecture notes in computer science, Deep Blue (University of Michigan) and USENIX Security Symposium.
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.