Daniel Moghimi

1.7k citations
20 papers · 602 indexed · h-index 11

Impact in

Papers in

Daniel Moghimi

19 papers receiving 575 citations

Peers

Daniel Moghimi
Comparison fields: 5 of 26
  • Hardware and Architecture 217
  • Signal Processing 301
  • Artificial Intelligence 526
  • Computer Networks and Communications 127
  • Information Systems 121
Replace Clémentine Maurice with:
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Dmitry Evtyushkin United States
Marina Minkin United States
David Kohlbrenner United States
Mengjia Yan United States
Johannes Götzfried Germany
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Onur Acıiçmez United States
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Citations per field
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Citations per year

Countries citing papers authored by Daniel Moghimi

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Moghimi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Daniel Moghimi, 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 Daniel Moghimi Line = papers co-authored together Daniel Moghimi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20244
2 20249
3 20242
4 202316
5 202214
6 202220
7
Swivel: Hardening WebAssembly against Spectre.
20213
8
Medusa: Microarchitectural data leakage via automated attack synthesis
202020
9 20205
10 2020108
11 202038
12
TPM-FAIL: TPM meets Timing and Lattice Attacks
20194
13 2019108
14 2019160
15 20197
16 201841
17 201817
18 201825
19
Side-Channel Attacks on Intel SGX: How SGX Amplifies The Power of Cache Attack
20171
20 20160

About Daniel Moghimi

Daniel Moghimi is a scholar working on Hardware and Architecture, Signal Processing, Artificial Intelligence, Information Systems and Computer Networks and Communications, having authored 20 papers that have together received 602 indexed citations. Recurring topics across this work include Security and Verification in Computing (18 papers), Physical Unclonable Functions (PUFs) and Hardware Security (9 papers), Advanced Malware Detection Techniques (8 papers), Cloud Data Security Solutions (7 papers), Diamond and Carbon-based Materials Research (3 papers), Cryptographic Implementations and Security (3 papers), Cryptography and Data Security (2 papers) and Semiconductor materials and devices (2 papers). The work is most often cited by research in Hardware and Architecture (217 citations), Signal Processing (301 citations), Artificial Intelligence (526 citations), Computer Networks and Communications (127 citations) and Information Systems (121 citations). Daniel Moghimi has collaborated with scholars based in United States, Germany and Australia. Frequent co-authors include Michael Schwarz, Jo Van Bulck, Berk Sunar, Daniel Gruss, Moritz Lipp, Daniel Genkin, Yuval Yarom, Thomas Eisenbarth, Thomas Prescher and Julian Stecklina. Their work appears in journals such as IACR Transactions on Cryptographic Hardware and Embedded Systems, IEEE Micro, International Journal of Parallel Programming, SHILAP Revista de lepidopterología and USENIX Security Symposium.

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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