Nabíl Schear

451 citations
20 papers · 317 · h-index 10

Impact in

Papers in

Nabíl Schear

20 papers receiving 301 citations

Peers

Nabíl Schear
Comparison fields: 5 of 28
  • Signal Processing 130
  • Computer Networks and Communications 173
  • Artificial Intelligence 231
  • Information Systems 143
  • Hardware and Architecture 23
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Nabíl Schear relative to Joshua Schiffman United States Joshua Schiffman's profile →
Citations per field
00.5×2.9×
Joshua Schiffman · 1×
Citations per year

Countries citing papers authored by Nabíl Schear

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with Nabíl Schear Line = papers co-authored together Nabíl Schear links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 200952
2 201449
3 201236
4 201632
5 201731
6 201027
7
Glavlit: Preventing Exfiltration at Wire Speed.
200621
8 200817
9 201610
10 20179
11 20168
12 20097
13 20087
14
Secure and Resilient Cloud Computing for the Department of Defense
20153
15
Automated Provenance Analytics: A Regular Grammar Based Approach with Applications in Security.
20172
16 20162
17 20101
18
Preventing encrypted traffic analysis
20111
19
Security and Privacy Assurance Research (SPAR) Pilot Final Report
20151
20 20161

About Nabíl Schear

Nabíl Schear is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Signal Processing and Information Systems and Management, having authored 20 papers that have together received 317 indexed citations. Recurring topics across this work include Internet Traffic Analysis and Secure E-voting (7 papers), Advanced Malware Detection Techniques (6 papers), Network Security and Intrusion Detection (6 papers), Cloud Data Security Solutions (5 papers), Security and Verification in Computing (5 papers), Cryptography and Data Security (4 papers), Scientific Computing and Data Management (3 papers) and Network Traffic and Congestion Control (3 papers). The work is most often cited by research in Signal Processing (130 citations), Computer Networks and Communications (173 citations), Artificial Intelligence (231 citations), Information Systems (143 citations) and Hardware and Architecture (23 citations). Nabíl Schear has collaborated with scholars based in United States and Vietnam. Frequent co-authors include Nikita Borisov, Emily Shen, Arkady Yerukhimovich, Sophia Yakoubov, Thomas Moyer, Vijay Gadepally, Samuel T. King, Negar Kiyavash, Xun Gong and David M. Nicol. Their work appears in journals such as Big Data, ACM SIGPLAN Notices, Lecture notes in computer science and 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.

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