Journal of Mathematical Cryptology

242 papers and 1.5k indexed citations i.

About

The 242 papers published in Journal of Mathematical Cryptology in the last decades have received a total of 1.5k indexed citations. Papers published in Journal of Mathematical Cryptology usually cover Artificial Intelligence (224 papers), Information Systems (72 papers) and Computational Theory and Mathematics (59 papers) specifically the topics of Coding theory and cryptography (162 papers), Cryptography and Data Security (121 papers) and Cryptographic Implementations and Security (93 papers). The most active scholars publishing in Journal of Mathematical Cryptology are Rachel Player, M. Albrecht, David Jao, Jérôme Plût, Luca De Feo, Pierrick Gaudry, Andrew M. Childs, Vladimir Soukharev, Thomas Vidick and Alexander Ushakov.

In The Last Decade

Fields of papers published in Journal of Mathematical Cryptology

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers published in Journal of Mathematical Cryptology. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers published in Journal of Mathematical Cryptology.

Countries where authors publish in Journal of Mathematical Cryptology

Since Specialization
Citations

This map shows the geographic impact of research published in Journal of Mathematical Cryptology. 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 papers published in Journal of Mathematical Cryptology with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Journal of Mathematical Cryptology more than expected).

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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