World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
73
Citations
29023
World Ranking
1553
National Ranking
809

Research.com Recognitions

  • 2008 - Fellow of Alfred P. Sloan Foundation

Overview

Tadayoshi Kohno is affiliated with the University of Washington in the United States. Their research spans multiple domains within computer science and social sciences, focusing particularly on privacy, security, and data protection. Kohno's work covers a range of topics including the ethics and social impacts of AI, privacy-preserving technologies, adversarial robustness in machine learning, and digital contact tracing related to COVID-19.

Their scholarly output includes publications in recognized venues such as arXiv (Cornell University), IEEE Security & Privacy, Proceedings on Privacy Enhancing Technologies, and the Proceedings of the AAAI/ACM Conference on AI Ethics and Society.

Frequent publication venues are as follows:

  • arXiv (Cornell University)
  • IEEE Security & Privacy
  • Proceedings on Privacy Enhancing Technologies
  • Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  • AI and Ethics

Frequently collaborating co-authors include:

  • Franziska Roesner
  • Lucy Simko
  • Mattea Sim
  • Elissa M. Redmiles
  • Inyoung Cheong

The main fields of study for Kohno's research are:

  • Computer Science
  • Social Sciences

Subfields within these areas include:

  • Artificial Intelligence
  • Sociology and Political Science
  • Information Systems
  • Safety Research
  • Computer Vision and Pattern Recognition

Key research topics addressed by Kohno are:

  • Privacy, Security, and Data Protection
  • Ethics and Social Impacts of AI
  • Privacy-Preserving Technologies in Data
  • Adversarial Robustness in Machine Learning
  • COVID-19 Digital Contact Tracing
  • Face recognition and analysis
  • Anomaly Detection Techniques and Applications

Recent notable publications include:

  • PACT: Privacy Sensitive Protocols and Mechanisms for Mobile Contact Tracing, 2020, arXiv (Cornell University)
  • Smart Devices in Airbnbs: Considering Privacy and Security for both Guests and Hosts, 2020, Proceedings on Privacy Enhancing Technologies
  • COVID-19 Contact Tracing and Privacy: Studying Opinion and Preferences, 2020, arXiv (Cornell University)
  • LLM Platform Security: Applying a Systematic Evaluation Framework to OpenAI's ChatGPT Plugins, 2024, Proceedings of the AAAI/ACM Conference on AI Ethics and Society
  • Safety, Security, and Privacy Threats Posed by Accelerating Trends in the Internet of Things, 2020, arXiv (Cornell University)

Kohno was recognized as a Fellow of the Alfred P. Sloan Foundation in 2008.

Best Publications

  • Experimental Security Analysis of a Modern Automobile

    Karl Koscher;Alexei Czeskis;Franziska Roesner;Shwetak Patel

  • Robust Physical-World Attacks on Deep Learning Visual Classification

    Kevin Eykholt;Ivan Evtimov;Earlence Fernandes;Bo Li

  • Comprehensive experimental analyses of automotive attack surfaces

    Stephen Checkoway;Damon McCoy;Brian Kantor;Danny Anderson

  • Remote physical device fingerprinting

    T. Kohno;A. Broido;K.C. Claffy

  • Searchable encryption revisited: consistency properties, relation to anonymous IBE, and extensions

    Michel Abdalla;Mihir Bellare;Dario Catalano;Eike Kiltz

  • Searchable Encryption Revisited: Consistency Properties, Relation to Anonymous IBE, and Extensions

    Michel Abdalla;Mihir Bellare;Dario Catalano;Eike Kiltz

  • Pacemakers and Implantable Cardiac Defibrillators: Software Radio Attacks and Zero-Power Defenses

    D. Halperin;T.S. Heydt-Benjamin;B. Ransford;S.S. Clark

  • Analysis of an electronic voting system

    T. Kohno;A. Stubblefield;A.D. Rubin;D.S. Wallach

  • Cryptography Engineering: Design Principles and Practical Applications

    Niels Ferguson;Bruce Schneier;Tadayoshi Kohno

  • A theoretical treatment of related-key attacks: RKA-PRPs, RKA-PRFs, and applications

    Mihir Bellare;Tadayoshi Kohno

  • Robust Physical-World Attacks on Deep Learning Models

    Ivan Evtimov;Kevin Eykholt;Earlence Fernandes;Tadayoshi Kohno

  • Security and Privacy for Implantable Medical Devices

    D. Halperin;T. Kohno;T.S. Heydt-Benjamin;K. Fu

  • ITS4: a static vulnerability scanner for C and C++ code

    J. Viega;J.T. Bloch;Y. Kohno;G. McGraw

  • Vanish: increasing data privacy with self-destructing data

    Roxana Geambasu;Tadayoshi Kohno;Amit A. Levy;Henry M. Levy

  • Detecting and defending against third-party tracking on the web

    Franziska Roesner;Tadayoshi Kohno;David Wetherall

  • Low-resource routing attacks against tor

    Kevin Bauer;Damon McCoy;Dirk Grunwald;Tadayoshi Kohno

  • Shining Light in Dark Places: Understanding the Tor Network

    Damon Mccoy;Kevin Bauer;Dirk Grunwald;Tadayoshi Kohno

  • Security and privacy for augmented reality systems

    Franziska Roesner;Tadayoshi Kohno;David Molnar

  • Robust Physical-World Attacks on Machine Learning Models.

    Ivan Evtimov;Kevin Eykholt;Earlence Fernandes;Tadayoshi Kohno

  • Physical Adversarial Examples for Object Detectors

    Dawn Song;Kevin Eykholt;Ivan Evtimov;Earlence Fernandes

  • Searchable encryption revisited

    Michel Abdalla;Mihir Bellare;Dario Catalano;Eike Kiltz

Frequent Co-Authors

Franziska Roesner
Franziska Roesner University of Washington
Mihir Bellare
Mihir Bellare University of California, San Diego
Bruce Schneier
Bruce Schneier Harvard University
Kevin Fu
Kevin Fu University of Michigan–Ann Arbor
David Molnar
David Molnar Microsoft (United States)
David Wetherall
David Wetherall Google (United States)
Henry M. Levy
Henry M. Levy University of Washington
John Kelsey
John Kelsey National Institute of Standards and Technology
Dawn Song
Dawn Song University of California, Berkeley
Arvind Krishnamurthy
Arvind Krishnamurthy University of Washington

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