World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
35
Citations
10411
World Ranking
11438
National Ranking
4698

Overview

David Molnar is affiliated with Microsoft in the United States and conducts research largely within the domain of social sciences. Their work spans several interconnected fields including political science and international relations, artificial intelligence, sociology and political science, geography, planning and development, as well as anthropology.

Their research touches on various topics such as Central European and Russian historical studies, historical geopolitical and social dynamics, privacy-preserving technologies in data, privacy, security and data protection, cryptography and data security, historical influence and diplomacy, and Hungarian social, economic, and educational studies.

Molnar has contributed to academic literature through several papers published in a range of venues. Recent publications include:

  • CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models, 2024, arXiv (Cornell University)
  • CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models, 2024, arXiv (Cornell University)
  • FILEFALVI FILICZKI JÁNOS ALBUM AMICORUMÁNAK MAGYAR VONATKOZÁSÚ BEJEGYZÉSEI, 2021, Gerundium
  • Klikk-keresési módszer alkalmazása az MTMT adatbázisban, 2020, Multidiszciplináris Tudományok
  • Az első magyarországi képvers? Filefalvi Filiczki János három képverséről, 2022, Magyar Könyvszemle

Their work has been published most frequently in:

  • arXiv (Cornell University)
  • Az Eszterházy Károly Katolikus Egyetem Történelemtudományi Doktori Iskolájának kiadványai. Konferenciák, műhelybeszélgetések
  • Gerundium
  • Multidiszciplináris Tudományok
  • Magyar Könyvszemle

David Molnar collaborates regularly with a number of coauthors, including:

  • Sahana Chennabasappa
  • Cyrus Nikolaidis
  • Daniel S. Song
  • Shengye Wan
  • Spencer Whitman

Best Publications

  • Automated Whitebox Fuzz Testing.

    Patrice Godefroid;Michael Y. Levin;David A. Molnar

  • Privacy and security in library RFID: issues, practices, and architectures

    David Molnar;David Wagner

  • SAGE: whitebox fuzzing for security testing

    Patrice Godefroid;Michael Y. Levin;David Molnar

  • The free haven project: distributed anonymous storage service

    Roger Dingledine;Michael J. Freedman;David Molnar

  • Homomorphic Signature Schemes

    Robert Johnson;David Molnar;Dawn Xiaodong Song;David Wagner

  • Security and Privacy Issues in E-passports

    A. Juels;D. Molnar;D. Wagner

  • A scalable, delegatable pseudonym protocol enabling ownership transfer of RFID tags

    David Molnar;Andrea Soppera;David Wagner

  • Enabling security in cloud storage SLAs with CloudProof

    Raluca Ada Popa;Jacob R. Lorch;David Molnar;Helen J. Wang

  • Security and privacy for augmented reality systems

    Franziska Roesner;Tadayoshi Kohno;David Molnar

  • Short chosen-prefix collisions for MD5 and the creation of a rogue CA certificate

    Marc Stevens;Alexander Sotirov;Jacob Appelbaum;Arjen K. Lenstra

  • Dynamic test generation to find integer bugs in x86 binary linux programs

    David Molnar;Xue Cong Li;David A. Wagner

  • The program counter security model: automatic detection and removal of control-flow side channel attacks

    David Molnar;Matt Piotrowski;David Schultz;David Wagner

  • Active property checking

    Patrice Godefroid;Michael Y. Levin;David A. Molnar

  • SAGE: Whitebox Fuzzing for Security Testing: SAGE has had a remarkable impact at Microsoft.

    Patrice Godefroid;Michael Y. Levin;David Molnar

  • Billions and billions of constraints: whitebox fuzz testing in production

    Ella Bounimova;Patrice Godefroid;David Molnar

  • MD5 considered harmful today, creating a rogue CA certificate

    A. Sotirov;M. Stevens;J. Appelbaum;Arjen K. Lenstra

  • Fast and precise sanitizer analysis with BEK

    Pieter Hooimeijer;Benjamin Livshits;David Molnar;Prateek Saxena

  • Symbolic finite state transducers: algorithms and applications

    Margus Veanes;Pieter Hooimeijer;Benjamin Livshits;David Molnar

  • SCRIPTGARD: automatic context-sensitive sanitization for large-scale legacy web applications

    Prateek Saxena;David Molnar;Benjamin Livshits

  • Why we can't be bothered to read privacy policies models of privacy economics as a lemons market

    Tony Vila;Rachel Greenstadt;David Molnar

  • The program counter security model : Automatic detection and removal of control-flow side channel attacks

    David Molnar;Matt Piotrowski;David Schultz;David Wagner

Frequent Co-Authors

Pál Sümegi
Pál Sümegi University of Szeged
Benjamin Livshits
Benjamin Livshits Imperial College London
Margus Veanes
Margus Veanes Microsoft (United States)
David Wagner
David Wagner University of California, Berkeley
Tadayoshi Kohno
Tadayoshi Kohno University of Washington
Franziska Roesner
Franziska Roesner University of Washington
Levente Vitos
Levente Vitos Royal Institute of Technology
Eyal Ofek
Eyal Ofek Microsoft (United States)
Helen J. Wang
Helen J. Wang Microsoft (United States)
Balazs Sumegi
Balazs Sumegi University of Pecs

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