Nabíl Schear
Impact in
- Signal Processing top 10%
- Advanced Malware Detection Techniques
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- Network Security and Intrusion Detection
Papers in
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- Internet Traffic Analysis and Secure E-voting 5
- Security and Verification in Computing 4
- Cryptography and Data Security 3
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- Network Security and Intrusion Detection 4
- Network Traffic and Congestion Control 3
- Co-authors
- Thomas Moyer (5 shared papers)Arkady Yerukhimovich (4 shared papers)Emily Shen (2 shared papers)Sophia Yakoubov (3 shared papers)Vijay Gadepally (2 shared papers)David M. Nicol (2 shared papers)Samuel T. King (1 shared paper)Qing Zhang (1 shared paper)
- Journals
- SIMULATION (1 paper)
- Partner nations
- United StatesVietnam
In The Last Decade
Nabíl Schear
14 papers receiving 197 citations
Peers
Comparison fields: 5 of 24
- Signal Processing 93
- Computer Networks and Communications 115
- Information Systems 106
- Artificial Intelligence 144
- Software 7
Countries citing papers authored by Nabíl Schear
This map shows the geographic impact of Nabíl Schear'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 Nabíl Schear with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nabíl Schear more than expected).
Fields of papers citing papers by Nabíl Schear
This network shows the impact of papers produced by Nabíl Schear. 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 Nabíl Schear. The network helps show where Nabíl Schear may publish in the future.
Co-authors
The 25 scholars most cited alongside Nabíl Schear, 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 | 2009 | 42 | |
| 2 | 2014 | 39 | |
| 3 | 2017 | 28 | |
| 4 | 2016 | 27 | |
| 5 | 2010 | 21 | |
| 6 | Glavlit: Preventing Exfiltration at Wire Speed. | 2006 | 19 |
| 7 | 2009 | 7 | |
| 8 | 2017 | 7 | |
| 9 | 2008 | 7 | |
| 10 | 2016 | 6 | |
| 11 | Secure and Resilient Cloud Computing for the Department of Defense | 2015 | 3 |
| 12 | Automated Provenance Analytics: A Regular Grammar Based Approach with Applications in Security. | 2017 | 2 |
| 13 | Preventing encrypted traffic analysis | 2011 | 1 |
| 14 | 2016 | 1 | |
| 15 | Security and Privacy Assurance Research (SPAR) Pilot Final Report | 2015 | 0 |
About Nabíl Schear
Nabíl Schear is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Information Systems and Management and Signal Processing, having authored 15 papers that have together received 210 indexed citations. Recurring topics across this work include Cloud Data Security Solutions (5 papers), Internet Traffic Analysis and Secure E-voting (5 papers), Security and Verification in Computing (4 papers), Network Security and Intrusion Detection (4 papers), Advanced Malware Detection Techniques (3 papers), Scientific Computing and Data Management (3 papers), Cryptography and Data Security (3 papers) and Network Traffic and Congestion Control (3 papers). The work is most often cited by research in Signal Processing (93 citations), Computer Networks and Communications (115 citations), Information Systems (106 citations), Artificial Intelligence (144 citations) and Software (7 citations). Nabíl Schear has collaborated with scholars based in United States and Vietnam. Frequent co-authors include Thomas Moyer, Arkady Yerukhimovich, Emily Shen, Sophia Yakoubov, Vijay Gadepally, David M. Nicol, Samuel T. King, Qing Zhang, Wajih Ul Hassan and Kevin Butler. Their work appears in journals such as SIMULATION.
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.