Gil Segev
- Artificial Intelligence top 5%
- Computational Theory and Mathematics top 5%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Moni NaorGilad AsharovMichael ZohnerThomas SchneiderBenny PinkasZvika BrakerskiMichael SchapiraScott Shenker
- Topics
- Cryptography and Data Security (34 papers)Complexity and Algorithms in Graphs (19 papers)Cryptographic Implementations and Security (13 papers)
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsComputer Networks and Communications
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Information TheoryCommunications of the ACM
- Partner nations
- IsraelUnited StatesGermany
In The Last Decade
Gil Segev
36 papers receiving 492 citations
Peers
Comparison fields: 5 of 39
- Artificial Intelligence 444
- Computational Theory and Mathematics 156
- Computer Networks and Communications 114
- Information Systems 96
- Computer Vision and Pattern Recognition 80
Countries citing papers authored by Gil Segev
This map shows the geographic impact of Gil Segev'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 Gil Segev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gil Segev more than expected).
Fields of papers citing papers by Gil Segev
This network shows the impact of papers produced by Gil Segev. 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 Gil Segev. The network helps show where Gil Segev may publish in the future.
Co-authorship network of co-authors of Gil Segev
This figure shows the co-authorship network connecting the top 25 collaborators of Gil Segev. A scholar is included among the top collaborators of Gil Segev 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 Gil Segev. Gil Segev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 13 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 11 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 3 | |
| 10 | 5 | |
| 11 | 46 | |
| 12 | Phasing: Private Set Intersection using Permutation-based Hashing. | 82 |
| 13 | Non-Malleable Extractors with Short Seeds and Applications to Privacy Amplification. | 1 |
| 14 | 14 | |
| 15 | 2 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 6 | |
| 19 | 22 | |
| 20 | 0 |
About Gil Segev
Gil Segev is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Computer Networks and Communications, having authored 38 papers that have together received 509 indexed citations. Recurring topics across this work include Cryptography and Data Security (34 papers), Complexity and Algorithms in Graphs (19 papers) and Cryptographic Implementations and Security (13 papers). The work is most often cited by research in Artificial Intelligence (444 citations), Computational Theory and Mathematics (156 citations) and Computer Networks and Communications (114 citations). Gil Segev has collaborated with scholars based in Israel, United States and Germany. Frequent co-authors include Moni Naor, Gilad Asharov, Michael Zohner, Thomas Schneider, Benny Pinkas, Zvika Brakerski, Michael Schapira, Scott Shenker, Ilya Mironov and Ilan Komargodski. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Information Theory and Communications of the ACM.
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.