Emilia Käsper
- Artificial Intelligence top 10%
- Information Systems top 10%
- Computer Networks and Communications
- Signal Processing
- Computer Vision and Pattern Recognition
- Co-authors
- Peter SchwabeBruno PouliquenCamelia IgnatRalf SteinbergerDavid AdrianJuraj SomorovskyShaanan CohneyChristof Paar
- Topics
- Cryptographic Implementations and Security (4 papers)Internet Traffic Analysis and Secure E-voting (2 papers)Advanced Malware Detection Techniques (2 papers)
- Journals
- Lecture notes in computer scienceUCL Discovery (University College London)DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
- Partner nations
- United StatesBelgiumNetherlands
In The Last Decade
Emilia Käsper
6 papers receiving 128 citations
Peers
Comparison fields: 5 of 19
- Artificial Intelligence 124
- Information Systems 48
- Computer Networks and Communications 36
- Signal Processing 33
- Computer Vision and Pattern Recognition 29
Countries citing papers authored by Emilia Käsper
This map shows the geographic impact of Emilia Käsper'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 Emilia Käsper with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Emilia Käsper more than expected).
Fields of papers citing papers by Emilia Käsper
This network shows the impact of papers produced by Emilia Käsper. 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 Emilia Käsper. The network helps show where Emilia Käsper may publish in the future.
Co-authorship network of co-authors of Emilia Käsper
This figure shows the co-authorship network connecting the top 25 collaborators of Emilia Käsper. A scholar is included among the top collaborators of Emilia Käsper 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 Emilia Käsper. Emilia Käsper is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Certificate Transparency Version 2.0 | 5 |
| 2 | DROWN: Breaking TLS using SSLv2 | 61 |
| 3 | The dangers of composing anonymous channels | 1 |
| 4 | Faster and Timing-Attack Resistant AES-GCM | 33 |
| 5 | 10 | |
| 6 | 35 |
About Emilia Käsper
Emilia Käsper is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 6 papers that have together received 145 indexed citations. Recurring topics across this work include Cryptographic Implementations and Security (4 papers), Internet Traffic Analysis and Secure E-voting (2 papers) and Advanced Malware Detection Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (124 citations), Signal Processing (33 citations) and Information Systems (48 citations). Emilia Käsper has collaborated with scholars based in United States, Belgium and Netherlands. Frequent co-authors include Peter Schwabe, Bruno Pouliquen, Camelia Ignat, Ralf Steinberger, David Adrian, Juraj Somorovsky, Shaanan Cohney, Christof Paar, Sebastian Schinzel and Yuval Shavitt. Their work appears in journals such as Lecture notes in computer science, UCL Discovery (University College London) and DROPS (Schloss Dagstuhl – Leibniz Center for Informatics).
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.