Research philosophy
I'm a systems security researcher. The central goal of my PhD research has been to design low-cost
defensive techniques for users deploying applications on public cloud infrastructure. I enjoy revisiting
long-standing, fundamental security problems with a fresh perspective (e.g., checking the integrity of
storage), especially as emerging technologies like confidential computing continue to radically reshape
the way applications are deployed on the cloud, edge, and everything in between. I also enjoy
taking a more visionary perspective, identifying imminent security problems and designing for the future
(e.g., developing flexible security protocols for next-gen storage, memory, and network devices).
My research involves building and benchmarking real-world systems---primarily secure file systems and
block device drivers. My toolkit often includes techniques in system design, applied cryptography, and
formal optimization. I leverage deep insights about operating system internals to design optimized data
structures and algorithms, apply optimization techniques as both a system design methodology and an
evaluation framework, and perform deep explorations into trade-off spaces to identify where certain
designs perform well or begin to break down. Generally speaking, I will find, learn, and use any tool at
my disposal to solve the problem at hand. I often draw connections between communities, blending
techniques in creative ways to reason about security problems in ways that were previously unexplored.
My recent research best reflects this philosophy. For example, I recently revisited the fundamental
problem of providing integrity protection over
untrusted storage devices---this time in the context of modern confidential virtual machines,
which introduce new trust assumptions and performance constraints. I demonstrated that while
state-of-the-art integrity protocols are theoretically efficient, their hashing costs become prohibitive
in practice. I formulated this as an optimization problem, then designed a new adaptive data structure
that learns and exploits workload patterns to reduce integrity verification costs. Building on this, I
then leveraged asynchronous techniques (which are
a building block of modern storage systems) to break through performance ceilings by carefully (and
securely) scheduling integrity verification work. In past work, I have also examined vulnerabilities and defenses in emerging software-defined
networking
(SDN) infrastructure, and designed robust defenses for IoT devices, among other topics.
I care deeply about real-world impact and strive to build usable, well-documented prototypes that run on
real systems. All of my research artifacts are open-sourced to
enable reproducibility and independent study.
Publications
Efficient Storage Integrity in Adversarial Settings
Quinn Burke, Ryan Sheatsley, Yohan Beugin, Eric Pauley, Owen Hines, Michael Swift, and
Patrick McDaniel
IEEE Symposium on Security and Privacy (S&P), 2025
PDF
arXiv
DOI
On Scalable Integrity Checking For Secure Cloud Disks
Quinn Burke, Ryan Sheatsley, Rachel King, Owen Hines, Michael Swift, and Patrick
McDaniel
USENIX Conference on File and Storage Technologies (FAST), 2025
PDF
arXiv
DOI
EIPSIM: Modeling Secure IP Address Allocation at Cloud Scale
Eric Pauley, Kyle Domico, Blaine Hoak, Ryan Sheatsley,
Quinn Burke, Yohan Beugin, Engin
Kirda, and Patrick McDaniel
Network and Distributed System Security Symposium (NDSS), 2025
PDF
arXiv
Securing Cloud File Systems with Trusted Execution
Quinn Burke, Yohan Beugin, Blaine Hoak, Rachel King, Eric Pauley, Ryan Sheatsley,
Mingli Yu, Ting He, Thomas La Porta,
and Patrick McDaniel
IEEE Transactions on Dependable and Secure Computing (TDSC), 2024
PDF
arXiv
DOI
ParTEETor: A System for Partial Deployments of TEEs within Tor
Rachel King,
Quinn Burke, Yohan Beugin, Blaine Hoak, Kunyang Li, Eric Pauley, Ryan
Sheatsley, and Patrick McDaniel
Workshop on Privacy in the Electronic Society (WPES) @ ACM CCS, 2024
PDF
Stealthy Misreporting Attacks Against Load Balancing
Mingli Yu,
Quinn Burke, Thomas La Porta, and Patrick McDaniel
IEEE/ACM Transactions on Networking (TON), 2024
PDF
DOI
Efficient Host Intrusion Detection using Hyperdimensional Computing
Yujin Nam, Rachel King,
Quinn Burke, Minxuan Zhou, Patrick McDaniel, and Tajana
Rosing
Workshop on Cyber Threat Intelligence and Hunting (CyberHunt) @ IEEE BigData, 2024
PDF
mMLSnet: Multilevel Security Network With Mobility (Best paper runner-up)
Mingli Yu,
Quinn Burke, Thomas La Porta, and Patrick McDaniel
IEEE Military Communications Conference (MILCOM), 2023
PDF
DOI
Joint Caching and Routing in Cache Networks with Arbitrary Topology
Tian Xie, Sanchal Thakkar, Ting He, Patrick McDaniel, and
Quinn Burke
IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023
PDF
DOI
Systematic Evaluation of Geolocation Privacy Mechanisms
Alban Héon, Ryan Sheatsley,
Quinn Burke, Blaine Hoak, Eric Pauley, Yohan Beugin, and
Patrick McDaniel
Preprint, 2023
PDF
arXiv
Enforcing Multilevel Security Policies in Unstable Networks
Quinn Burke, Fidan Mehmeti, Rahul George, Trent Jaeger, Thomas La Porta, and Patrick
McDaniel
IEEE Transactions on Network and Service Management (TNSM), 2022
PDF
DOI
Privacy-Preserving Protocols for Smart Cameras and Other IoT Devices
Yohan Beugin,
Quinn Burke, Blaine Hoak, Ryan Sheatsley, Eric Pauley, Gang Tan, Syed
Rafiul Hussain, and Patrick McDaniel
Preprint, 2022
PDF
arXiv
Building a Privacy-Preserving Smart Camera System
Yohan Beugin,
Quinn Burke, Blaine Hoak, Ryan Sheatsley, Eric Pauley, Gang Tan, Syed
Rafiul Hussain, and Patrick McDaniel
Privacy Enhancing Technologies Symposium (PETS), 2022
PDF
arXiv
DOI
Joint Caching and Routing in Cache Networks with Arbitrary Topology
Tian Xie, Sanchal Thakkar, Ting He, Patrick Drew Mcdaniel, and
Quinn Burke
IEEE International Conference on Distributed Computing Systems (ICDCS), 2022
PDF
DOI
Measuring and Mitigating the Risk of IP Reuse on Public Clouds
Eric Pauley, Ryan Sheatsley, Blaine Hoak,
Quinn Burke, Yohan Beugin, and Patrick
McDaniel
IEEE Symposium on Security and Privacy (S&P), 2022
PDF
arXiv
DOI
FAQ
A Machine Learning and Computer Vision Approach to Geomagnetic Storm Forecasting
Kyle Domico, Ryan Sheatsley, Yohan Beugin,
Quinn Burke, and Patrick McDaniel
Machine Learning in Heliophysics Conference (ML-Helio), 2022
PDF
arXiv
DOI
Misreporting Attacks Against Load Balancers in Software-Defined Networking
Quinn Burke, Patrick McDaniel, Thomas La Porta, Mingli Yu, and Ting He
Mobile Networks and Applications (MONET), Springer, 2021
PDF
DOI
Flow Table Security in SDN: Adversarial Reconnaissance and Intelligent Attacks
Mingli Yu, Tian Xie, Ting He, Patrick McDaniel, and
Quinn Burke
IEEE/ACM Transactions on Networking (TON), 2021
PDF
DOI
MLSNet: A Policy Complying Multilevel Security Framework for Software Defined
Networking
Stefan Achleitner,
Quinn Burke, Patrick McDaniel, Trent Jaeger, Thomas La Porta, and
Srikanth Krishnamurthy
IEEE Transactions on Network and Service Management (TNSM), 2021
PDF
arXiv
DOI
Misreporting Attacks in Software-Defined Networking
Quinn Burke, Patrick McDaniel, Thomas La Porta, Mingli Yu, and Ting He
International Conference on Security and Privacy in Communication Networks (SecureComm), 2020
PDF
DOI
Flow Table Security in SDN: Adversarial Reconnaissance and Intelligent Attacks
Mingli Yu, Ting He, Patrick McDaniel, and
Quinn Burke
IEEE International Conference on Computer Communications (INFOCOM), 2020
PDF
DOI
Complete list available on the publications page.