Ryan Sheatsley, PhD

I am a postdoc at the Department of Computer Sciences at the University of Wisconsin-Madison. I am member of MadS&P and advised by Prof. Patrick McDaniel. Previously, I earned my Ph.D. in Computer Sciences at the University of Wisconsin-Madison with M.S. and B.S. in computer science and engineering from the Pennsylvania State University.

My research is at the intersection of computer security and machine learning. I investigate the risks of deploying machine learning systems in security-centric domains, how their robustness can be measured at scale, and their applications towards novel security problems. I also apply computer security principles to radiation detection, Internet measurement, and Internet of Things.

Address: 1210 W. Dayton St., Room 2253, Madison, WI 53706, USA
Email: ryan@sheatsley.me

Publications

Systematic Evaluation of Geolocation Privacy Mechanisms
Alban Héon, Ryan Sheatsley, Quinn Burke, Blaine Hoak, Eric Pauley, Yohan Beugin, Patrick McDaniel
arXiv, 2023

Characterizing the Modification Space of Signature IDS Rules
Ryan Guide, Eric Pauley, Yohan Beugin, Ryan Sheatsley, Patrick McDaniel
Proceedings of the IEEE Conference on Military Communications (MILCOM), 2023

The Space of Adversarial Strategies
Ryan Sheatsley*, Blaine Hoak*, Eric Pauley, Patrick McDaniel
Proceedings of the USENIX Security Symposium, 2023
*Equal contribution

Experimental tests of Gamma-ray Localization Aided with Machine-learning (GLAM) capabilities
Matthew Durbin, Ryan Sheatsley, Patrick McDaniel, Azaree Lintereur
Elsevier Journal of Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment (NIM-A), 2022

Measuring and Mitigating the Risk of IP Reuse on Public Clouds
Eric Pauley, Ryan Sheatsley, Blaine Hoak, Quinn Burke, Yohan Beugin, Patrick McDaniel
Proceedings of the IEEE Conference on Security and Privacy (S&P), 2022

A Machine Learning and Computer Vision Approach to Geomagnetic Storm Forecasting
Kyle Domico, Ryan Sheatsley, Yohan Beugin, Quinn Burke, Patrick McDaniel
Proceedings of the AGU Conference on Machine Learning in Heliophysics (ML-Helio), 2022

Adversarial Examples in Constrained Domains
Ryan Sheatsley, Nicolas Papernot, Michael Weisman, Gunjan Verma, Patrick McDaniel
IOS Press Journal of Computer Security (JCS), 2022

Building a Privacy-Preserving Smart Camera System
Yohan Beugin, Quinn Burke, Blaine Hoak, Ryan Sheatsley, Eric Pauley, Gang Tan, Syed Rafiul Hussain, Patrick McDaniel
Proceedings of Privacy Enhancing Technologies Symposium (PETS), 2022

Physics-based Misbehavior Detection System for V2X Communications
Alejandro Andrade Salazar, Patrick McDaniel, Ryan Sheatsley, Jonathan Petit
SAE International Journal of Connected and Automated Vehicles, 2022

HoneyModels: Machine Learning Honeypots
Ahmed Abdou, Ryan Sheatsley, Yohan Beugin, Tyler Shipp, Patrick McDaniel
Proceedings of the IEEE Conference on Military Communications (MILCOM), 2021

On the Robustness of Domain Constraints
Ryan Sheatsley, Blaine Hoak, Eric Pauley, Yohan Beugin, Michael Weisman, Patrick McDaniel
Proceedings of the ACM Conference on Computer and Communications Security (CCS), 2021

Feature Engineering: A Case Study For Radiation Source Localization In Complicated Environments
Matthew Durbin, Ryan Sheatsley, Patrick McDaniel, Azaree Lintereur
Proceedings of the Institute of Nuclear Materials Management Annual Meeting (INMM), 2021

Improving Radioactive Material Localization by Leveraging Cyber-Security Model Optimizations
Ryan Sheatsley, Matthew Durbin, Azaree Lintereur, Patrick McDaniel
IEEE Sensors, 2021

Evading Machine Learning-based Network Intrusion Detection Systems with GANs
Bolor-Erdene Zolbayar, Ryan Sheatsley, Patrick McDaniel
Game Theory and Machine Learning for Cyber Security
Charles A Kamhoua, Christopher D. Kiekintveld, Fei Fang, Quanyan Zhu (Editors), 2021

Generating Practical Adversarial Network Traffic Flows using NIDSGAN
Bolor-Erdene Zolbayar, Ryan Sheatsley, Patrick McDaniel, Michael Weisman, Sencun Zhu, Shitong Zhu, Srikanth Krishnamurthy
arXiv, 2020

Adversarial Planning
Valentin Vie, Ryan Sheatsley, Sophia Beyda, Sushrut Shringarputale, Kevin Chan, Trent Jaeger, Patrick McDaniel
arXiv, 2020

A Multi-Step Machine Learning Approach to Directional Gamma Ray Detection
Matthew Durbin, Ryan Sheatsley, Patrick McDaniel, Azaree Lintereur
Proceedings of the IEEE Conference on Nuclear Science and Medical Imaging (NSS/MIC), 2020

Development of Machine Learning Algorithms for Directional Gamma Ray Detection
Matthew Durbin, Ryan Sheatsley, Christopher Balbier, Tristan Grieve, Patrick McDaniel, Azaree Lintereur
Proceedings of the Institute of Nuclear Materials Management Annual Meeting (INMM), 2019
J.D. Williams Student Paper Award

Curie: Policy-based Secure Data Exchange
Z. Berkay Celik, Abbas Acar, Hidayet Aksu, Ryan Sheatsley, Patrick McDaniel, A Secuk Uluagac
Proceedings of the ACM Conference on Data and Application Security and Privacy (CODASPY), 2019

Application Transiency: Towards a Fair Trade of Personal Information for Application Services
Raquel Alvarez, Jake Levenson, Ryan Sheatsley, Patrick McDaniel
Proceedings of the EAI Conference on Security and Privacy in Communication Networks (SecureComm), 2019

Detection under Privileged Information
Z. Berkay Celik, Patrick McDaniel, Rauf Izmailov, Nicolas Papernot, Ryan Sheatsley, Raquel Alvarez, Ananthram Swami
Proceedings of the ACM ASIA Conference on Computer and Communications Security (ASIACCS), 2018

Network Traffic Obfuscation: An Adversarial Machine Learning Approach
Gunjan Verma, Ertugrul Ciftcioglu, Ryan Sheatsley, Kevin Chan, Lisa Scott
Proceedings of the IEEE Conference on Military Communications (MILCOM), 2018

A Vision Toward an Internet of Battlefield Things (IoBT): Autonomous Classifying Sensor Network
John Zhu, Egan McClave, Quan Pham, Sujay Polineni, Sam Reinhart, Ryan Sheatsley, Andrew Toth
United States Army Research Laboratory, 2018

Heterogeneous Information Sharing of Sensor Information in Contested Environments
Jason A Wampler, Chien Hsieh, Andrew Toth, Ryan Sheatsley
Proceedings of the SPIE Conference on Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR (SPIE), 2017

Cleverhans v1.0.0: an Adversarial Machine Learning Library
Nicolas Papernot, Ian Goodfellow, Ryan Sheatsley, Reuben Feinman, Patrick McDaniel
arXiv, 2016

Analyzing GAIAN Database (GaianDB) on a Tactical Network
Ryan Sheatsley, Andrew Toth
United States Army Research Laboratory, 2015