World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
89
Citations
54848
World Ranking
630
National Ranking
335

Research.com Recognitions

  • 2015 - ACM Fellow For contributions to computer and mobile systems security.

Overview

Patrick McDaniel is affiliated with the University of Wisconsin-Madison in the United States. Their research primarily spans the field of computer science, with a focus on subfields including computer networks and communications, artificial intelligence, information systems, signal processing, and sociology and political science.

The scientist's work covers a range of topics, notably network security and intrusion detection, advanced malware detection techniques, internet traffic analysis and secure e-voting, software-defined networks and 5G, adversarial robustness in machine learning, security and verification in computing, and privacy, security, and data protection.

Research output includes numerous publications in recognized venues. Frequent publication venues for their work include:

  • arXiv (Cornell University)
  • IEEE/ACM Transactions on Networking
  • Proceedings on Privacy Enhancing Technologies
  • ACM Transactions on Internet of Things
  • IEEE Transactions on Network and Service Management

They have co-authored extensively with several researchers, including:

  • Ryan Sheatsley
  • Blaine Hoak
  • Yohan Beugin
  • Quinn Burke
  • Bahman Zohuri

Selected recent papers authored or co-authored by Patrick McDaniel include:

  • "A survey on IoT platforms: Communication, security, and privacy perspectives," 2021, Computer Networks
  • "Real-time Analysis of Privacy-(un)aware IoT Applications," 2021, DOAJ (Directory of Open Access Journals)
  • "Who's Controlling My Device? Multi-User Multi-Device-Aware Access Control System for Shared Smart Home Environment," 2022, ACM Transactions on Internet of Things
  • "Adversarial examples for network intrusion detection systems," 2022, Journal of Computer Security
  • "Flow Table Security in SDN: Adversarial Reconnaissance and Intelligent Attacks," 2021, IEEE/ACM Transactions on Networking

In 2015, Patrick McDaniel was recognized as an ACM Fellow for contributions to computer and mobile systems security.

Best Publications

  • TaintDroid: An Information-Flow Tracking System for Realtime Privacy Monitoring on Smartphones

    William Enck;Peter Gilbert;Seungyeop Han;Vasant Tendulkar

  • The Limitations of Deep Learning in Adversarial Settings

    Nicolas Papernot;Patrick McDaniel;Somesh Jha;Matt Fredrikson

  • Practical Black-Box Attacks against Machine Learning

    Nicolas Papernot;Patrick McDaniel;Ian Goodfellow;Somesh Jha

  • Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks

    Nicolas Papernot;Patrick McDaniel;Xi Wu;Somesh Jha

  • Ensemble Adversarial Training: Attacks and Defenses

    Florian Tramèr;Alexey Kurakin;Nicolas Papernot;Ian J. Goodfellow

  • TaintDroid: an information-flow tracking system for realtime privacy monitoring on smartphones

    William Enck;Peter Gilbert;Byung-Gon Chun;Landon P. Cox

  • FlowDroid: precise context, flow, field, object-sensitive and lifecycle-aware taint analysis for Android apps

    Steven Arzt;Siegfried Rasthofer;Christian Fritz;Eric Bodden

  • Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples

    Nicolas Papernot;Patrick D. McDaniel;Ian J. Goodfellow

  • Semantically rich application-centric security in Android

    Machigar Ongtang;Stephen McLaughlin;William Enck;Patrick McDaniel

  • Security and Privacy Challenges in the Smart Grid

    P. McDaniel;S. McLaughlin

  • On lightweight mobile phone application certification

    William Enck;Machigar Ongtang;Patrick McDaniel

  • A study of android application security

    William Enck;Damien Octeau;Patrick McDaniel;Swarat Chaudhuri

  • Understanding Android Security

    W. Enck;M. Ongtang;P. McDaniel

  • Secure attribute-based systems

    Matthew Pirretti;Patrick Traynor;Patrick Mcdaniel;Brent Waters

  • Towards the Science of Security and Privacy in Machine Learning

    Nicolas Papernot;Patrick D. McDaniel;Arunesh Sinha;Michael P. Wellman

  • On the (Statistical) Detection of Adversarial Examples

    Kathrin Grosse;Praveen Manoharan;Nicolas Papernot;Michael Backes

  • IccTA: detecting inter-component privacy leaks in Android apps

    Li Li;Alexandre Bartel;Tegawende F. Bissyande;Jacques Klein

  • Technical Report on the CleverHans v2.1.0 Adversarial Examples Library

    Nicolas Papernot;Fartash Faghri;Nicholas Carlini;Ian Goodfellow

  • The Space of Transferable Adversarial Examples

    Florian Tramèr;Nicolas Papernot;Ian J. Goodfellow;Dan Boneh

  • Adversarial examples for malware detection

    Kathrin Grosse;Nicolas Papernot;Praveen Manoharan;Michael Backes

  • A Survey of BGP Security Issues and Solutions

    K. Butler;T.R. Farley;P. McDaniel;J. Rexford

  • Effective inter-component communication mapping in Android with Epicc: an essential step towards holistic security analysis

    Damien Octeau;Patrick McDaniel;Somesh Jha;Alexandre Bartel

Frequent Co-Authors

Nicolas Papernot
Nicolas Papernot University of Toronto
William Enck
William Enck North Carolina State University
Kevin R. B. Butler
Kevin R. B. Butler University of Florida
Patrick Traynor
Patrick Traynor University of Florida
Trent Jaeger
Trent Jaeger Pennsylvania State University
Thomas F. La Porta
Thomas F. La Porta Pennsylvania State University
Ananthram Swami
Ananthram Swami United States Army Research Laboratory
Somesh Jha
Somesh Jha University of Wisconsin–Madison
William Aiello
William Aiello University of British Columbia
Atul Prakash
Atul Prakash University of Michigan–Ann Arbor

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