Ünal Koçabas

802 citations
10 papers · 344 · h-index 9

Impact in

Papers in

Ünal Koçabas

10 papers receiving 338 citations

Peers

Ünal Koçabas
Comparison fields: 5 of 17
  • Hardware and Architecture 283
  • Cellular and Molecular Neuroscience 142
  • Electrical and Electronic Engineering 238
  • Artificial Intelligence 105
  • Computer Vision and Pattern Recognition 35
Replace Maximilian Hofer with:
Maximilian Hofer Germany
Lilas Alrahis United States
David M’Raïhi United States
Fatemeh Tehranipoor United States
Mudit Bhargava United States
Youhua Shi Japan
Abdelkarim Cherkaoui France
Dmitry Nedospasov Germany
Clemens Helfmeier Germany
Frederic Stumpf Germany
Ünal Koçabas relative to Maximilian Hofer Germany Maximilian Hofer's profile →
Citations per field
00.5×5.2×
Maximilian Hofer · 1×
Citations per year

Countries citing papers authored by Ünal Koçabas

Since Specialization
Citations

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

Fields of papers citing papers by Ünal Koçabas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ünal Koçabas. 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 Ünal Koçabas. The network helps show where Ünal Koçabas may publish in the future.

Co-authors

The 20 scholars most cited alongside Ünal Koçabas, 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 Ünal Koçabas Line = papers co-authored together Ünal Koçabas links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 201379
2 201166
3 201363
4 201136
5 201227
6 201024
7 201222
8 201014
9
PUFs: Myth, Fact or Busted? A Security Evaluation of Physically Unclonable Functions (PUFs) Cast in Silicon
201210
10 20113

About Ünal Koçabas

Ünal Koçabas is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering, Artificial Intelligence, Cellular and Molecular Neuroscience and Information Systems, having authored 10 papers that have together received 344 indexed citations. Recurring topics across this work include Physical Unclonable Functions (PUFs) and Hardware Security (8 papers), Integrated Circuits and Semiconductor Failure Analysis (4 papers), Neuroscience and Neural Engineering (3 papers), Coding theory and cryptography (3 papers), Advanced Memory and Neural Computing (3 papers), Cryptographic Implementations and Security (2 papers), Chaos-based Image/Signal Encryption (1 paper) and Cryptography and Residue Arithmetic (1 paper). The work is most often cited by research in Hardware and Architecture (283 citations), Cellular and Molecular Neuroscience (142 citations), Electrical and Electronic Engineering (238 citations), Artificial Intelligence (105 citations) and Computer Vision and Pattern Recognition (35 citations). Ünal Koçabas has collaborated with scholars based in Germany, Belgium and Japan. Frequent co-authors include Ahmad‐Reza Sadeghi, Patrick Koeberl, Ingrid Verbauwhede, Stefan Katzenbeisser, Christian Wachsmann, A. Das, Junfeng Fan, Geert-Jan Schrijen, Vincent van der Leest and Akashi Satoh. Their work appears in journals such as Journal of Cryptographic Engineering, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Lecture notes in computer science, Design, Automation, and Test in Europe and Lirias (KU Leuven).

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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