Michael J. Wiener

14 papers receiving 1.3k citations

Hit Papers

Authentication and authenticated key exchanges19922026200320141992100200300400500

Peers

Michael J. Wiener
Comparison fields: 5 of 56
  • Artificial Intelligence 1.2k
  • Information Systems 676
  • Computer Networks and Communications 570
  • Computer Vision and Pattern Recognition 387
  • Electrical and Electronic Engineering 116
Replace J.-J. Quisquater with:
J.-J. Quisquater Belgium
Tanja Lange Netherlands
Arjen K. Lenstra United States
Yuliang Zheng Australia
Hugo Krawczyk United States
Marc Jóye France
Serge Vaudenay Switzerland
Darrel Hankerson United States
Antoine Joux France
Jean-Jacques Quisquater Belgium
Michael J. Wiener relative to J.-J. Quisquater Belgium J.-J. Quisquater's profile →
Citations per field
00.5×2.6×
J.-J. Quisquater · 1×
Citations per year

Countries citing papers authored by Michael J. Wiener

Since Specialization
Citations

This map shows the geographic impact of Michael J. Wiener'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 Michael J. Wiener with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael J. Wiener more than expected).

Fields of papers citing papers by Michael J. Wiener

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael J. Wiener. 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 Michael J. Wiener. The network helps show where Michael J. Wiener may publish in the future.

Co-authorship network of co-authors of Michael J. Wiener

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Wiener. A scholar is included among the top collaborators of Michael J. Wiener 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 Michael J. Wiener. Michael J. Wiener is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
#WorkIndexed citations
1 5
2 1
3 5
4 1
5 4
6 14
7
Advances in cryptology, CRYPTO '99 : 19th Annual International Cryptology Conference, Santa Barbara, California, USA, August 15-19, 1999 : proceedings
5
8 277
9 209
10 43
11 2
12
Efficient DES Key Search
60
13
Authentication and authenticated key exchangesbreakdown →
555
14 316
15
Cryptanalysis of Short RSA Secret Exponents (Abstract).
1

About Michael J. Wiener

Michael J. Wiener is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 15 papers that have together received 1.5k indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (11 papers), Cryptography and Data Security (6 papers) and Chaos-based Image/Signal Encryption (6 papers). The work is most often cited by research in Artificial Intelligence (1.2k citations), Information Systems (676 citations) and Computer Networks and Communications (570 citations). Michael J. Wiener has collaborated with scholars based in Canada and United States. Frequent co-authors include Paul C. van Oorschot, Whitfield Diffie, Carlisle Adams, Yuan Gu, Harold J. Johnson, S.E. Tavares, Warwick Ford, Howard M. Heys and Clifford Liem. Their work appears in journals such as IEEE Transactions on Information Theory, Lecture notes in computer science and Journal of Cryptology.

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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