Robert J. Walls

147 Fuller Labs
Worcester, MA 01609
rjwalls@wpi.edu

The Cake Lab
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News

Students!: I am currently looking for motivated and qualified students. If you are a WPI student, please send me an email or stop by. If you are outside of WPI, I invite you to apply and then contact me. Use keyword fignewtons for a more rapid response.

About Me

I am an assistant professor in the Department of Computer Science at Worcester Polytechnic Institute and a proud member of The Cake Lab and the Applied Logic and Security research group. My current interests focus on systems security and performance and my projects often lie at the intersection of software and hardware. Checkout our lab’s project page to learn more about some of my current research projects. In the Fall of 2016, I brought in security researchers from around to the area to participate in New England Security Day.

Previously, I was a postdoctoral scholar in Department of Electrical Engineering and Computer Science at The Pennsylvania State University working with Prof. Patrick McDaniel. Before that, I attended the School of Computer Science at the University of Massachusetts advised by Prof. Brian Levine. My research at UMass focused on providing law enforcement with novel techniques for investigating crimes. You can find my thoughts on the difference between forensics and security here.

Current Projects

I’ve had the opportunity to work on a number of interesting research projects during my career. Checkout The Cake Lab’s website for the most up to date information about my work.

Capr-DL: Confidential and Private Deep Learning

Providing users with control over their personal data, while still allowing them to benefit from the utility of deep learning, is one of the key challenges of contemporary computer science. Our work on the Capr-DL project is focused on performing deep learning operations directly on a personal device, with a trusted framework, allowing both users to retain control over their private data and companies to retain control over their proprietary models.

RIPCORD: Model Execution Caching

The RIPCORD project proposes a new infrastructure for improving the performance of deep learning model serving. Our work explores the promise of model execution caching as a means for improving the performance of cloud-based deep inference serving. Model execution caching requires a CDN-like shared infrastructure designed for workloads that see requests for a large and diverse set of models. That is, a workload where the aggregate volume of requests is high but no single model is popular enough to merit a dedicated server.

Embedded Systems Security

Embedded systems form the core of critical infrastructure, perform auxiliary processing on mobile phones, and permeate homes as smart devices. Yet, embedded software security lags behind traditional desktop security. While myriad defenses exist for general-purpose systems (e.g., desktops and servers), embedded systems present several unique challenges for software security such as greater hardware diversity, limited resources (e.g. memory and power), and lack of support for common abstractions like virtual memory.

Our work in this area includes defenses for protecting embedded software from control-flow hijacking attacks (Recfish and Silhouette); FPGA architectures that balance the throughput and resource requirements of AES (Drab-Locus); and techniques for generating secure random numbers (Erhard-RNG).

Past Projects

Below are some of the previous projects I have had the privilege to work on.

Web Security and Privacy

Domain names have become the Internet’s de facto root of trust. In practice, they are also a root of insecurity as common security systems depend on the unfounded assumption that domain ownership remains constant; this leaves users vulnerable to exploitation when domain ownership changes. In our [Oakland 2016][oakland16] we find that many seemingly disparate security problems share a root cause in residual domain trust abuse.

Online advertising is one of those little annoyances that we all have to deal with. “Not so!” Said the plethora of ad blocking extensions promising to improve your browser experience. Not only do they block ads, they also claim to help preserve your privacy and protect you against the growing trend of malicious advertisements. In our IMC 2015 work my co-authors and I take a closer look at the most popular ad blocking software. We find that ad blockers are not quite what they appear to be.

Digital Forensics

Mobile phones contain evidence that is invaluable for criminal investigations. However, commercially-available forensic tools must be hand-tailored to each phone model. If no tools support the target phone, then extracting the phone’s information requires investigators to examine the stored data byte by byte. To address this problem, I’ve developed general algorithms and techniques for recovering information from phones even if the exact storage format is unknown or the data has been logically deleted.

DECODE is an inference engine that extracts meaningful information from raw byte streams. Read more about it here.

Liftr incorporates investigator feedback and relevance graphs to improve the results of inference engines like DEC0DE. Paper here.

Yapr parses the Yaffs File System commonly found on (older) Android phones. Yapr even has limited ability to reconstruct past versions of a file by leverage expired pages of flash memory.

Filtr implements the concept of block hash filtering using bloom filters. In short, Filtr will remove an repeated blocks of data in a raw byte stream. For flash-based devices, such as phones, Filtr often removes 50-90% of the raw data, saving precious time by limited the amount of data that needs to be examines. Read more about block hash filtering here.

Science of Security

Perhaps the most ambitious projects I’ve been involved with is the 10-year Cyber-Security Collaborative Research Alliance with the Army Research Laboratory, Penn State, Carnegie Mellon, UC Riverside, UC Davis, and Indiana University. The project’s mandate is to develop a new science of security. As part of this effort, I’ve worked on the foundation for representing operational and environmental knowledge—see my work on ontologies here—with the goal of reasoning about both current and future states to make optimal security decisions.

Improving the Process

Like all computer scientists, I am constantly on the lookout for tools or methods that will help me be more efficient in my work. Here are a few repositories that you may find helpful.

Latex Paper Template. Tired of wasting half an hour setting up your paper directory every time you start a new project? Try my paper template instead.

Slidify Tutorial. I am a big fan of presentations, R, and Markdown—Slidify beautifully combines all three. Check out my simple Slidify tutorial here.

Selected Publications

2020
Silhouette: Efficient Protected Shadow Stacks for Embedded Systems.
Jie Zhou, Yufei Du, Lele Ma, Zhuojia Shen, John Criswell, and Robert J. Walls.
Proc. USENIX Security Symposium.
2020
DRAB-LOCUS: An Area-Efficient AES Architecture for Hardware Accelerator Co-Location on FPGAs.
Jake Grycel and Robert J. Walls.
{IEEE International Symposium on Circuits and Systems}.
2019
Control-Flow Integrity for Real-Time Embedded Systems.
Robert J. Walls, Nicolas Brown, Thomas LeBaron, Bryan Ward, Craig A. Shue, and Hamed Okhravi.
Euromirco Conference on Real-Time Systems (ECRTS).
2016
Domain-Z: 28 Registrations Later.
Chaz Lever, Robert J. Walls, Yacin Nadji, David Dagon, Patrick McDaniel, and Manos Antonakakis.
IEEE Symposium on Security and Privacy.
2015
Measuring the Impact and Perception of Acceptable Advertisements.
Robert J. Walls, Eric D. Kilmer, Nathaniel Lageman, and Patrick D. McDaniel.
Proceedings of the ACM 2015 Internet Measurement Conference (IMC).
2013
Measurement and Analysis of Child Pornography Trafficking on P2P Networks.
Ryan Hurley, Swagatika Prusty, Hamed Soroush, Robert J. Walls, Jeannie Albrecht, Emmanuel Cecchet, Brian Neil Levine, Marc Liberatore, Brian Lynn, and Janis Wolak.
Proc. Intl. World Wide Web Conference (WWW).
2011
Effective Digital Forensics Research is Investigator-Centric.
Robert J. Walls, Brian Neil Levine, Marc Liberatore, and Clay Shields.
Proc. USENIX Workshop on Hot Topics in Security (HotSec).
2011
Forensic Triage for Mobile Phones with DEC0DE.
Robert J. Walls, Erik Learned-Miller, and Brian Neil Levine.
Proc. USENIX Security Symposium.