iSTELLAR and Aker at ICCAD

Our group presented two papers related to hardware security at the International Conference on Computer-Aided Design (ICCAD). ICCAD is a top-tier conference in electronic design automation. There is an increasing emphasis on hardware security at ICCAD (and most other hardware design research venues) in the past years.

Prof. Jeremy Blackstone presented our group’s first paper: iSTELLAR: intermittent Signature aTtenuation Embedded CRYPTO with Low-Level metAl Routing. iSTELLAR presents a defense against electromagnetic and power attacks on that combines circuit-level and physical-level mitigations from STELLAR with notion of computational blinking. The end result is a flexible defense that enables a tradeoff between power consumption with leakage mitigation. The work was done in collaboration with Prof. Shreyas Sen (Purdue), Dr. Debayan Das (Purdue/Intel), and Dr. Alric Althoff (Tortuga Logic).

Aker — an Egyptian god that guards the netherworld. Image by Jeff Dahl – Own work, CC BY-SA 4.0

Our group’s second paper — Aker: A Design and Verification Framework for Safe and Secure SoC Access Control — was presented by Andy Meza. Aker is a design and security verification framework for system on chip access control. Aker provides flexible hardware access control wrappers that monitor memory accesses. And it provides an extensible security verification environment that can generate a variety of hardware security based upon the threat model. This work was done in collaboration with Dr. Francesco Restuccia (Scuola Superiore Sant’Anna Pisa and soon to be UCSD!). The hardware designs and security properties are released for open use in our Aker repository.

Congrats to all the authors!

Related Links: iSTELLAR paper, Aker paper, Aker Repository

An Unconventional, Unexpected, Outstanding PhD

Dr. Alireza Khodamoradi successfully defended his PhD thesis “Reshaping Deep Neural Networks for Efficient Hardware Inference”. Ali’s PhD has been unconventional in many ways — starting from his admission into UCSD, his unrelenting desire to get a PhD, and his ability to constantly surprise and impress.

Ali’s UCSD journey started almost a decade ago. He was working at the time in a state prison and applied for the WES MAS in the first year of that program. He was rejected. As soon as he was notified of his rejection, Ali contacted me (as WES program director) asked what he could do to get in. I told him to take some UCSD Extension classes as I tell all students in this position.

Hiking to Shadow Lake during the Kastner Research Group Retreat.

For the majority of rejected candidates, they ignore this advice and I never see them again. Ali is unconventional. Not only did he enroll in classes, he also wanted to do some research. I gave him the opportunity to work in our Engineers for Exploration project to demonstrate his skills and more important show us that he was ready and willing to excel in a top graduate program. He volunteered as a researcher and did some really fantastic work as a researcher in the Intelligent Camera Trap project and eventually became the leader of the Angry Birds projects.

The following year, he applied again to the MAS program. He was accepted!

During the WES MAS program, Ali told me that he wanted to do a PhD. I told him that this was very unlikely, that it was not the intended path for WES MAS students, that it would be very challenging to transfer into the PhD program, and that there was no precedent for this. I told him that if he really wanted this, he had to continue to do well in the program and excel in research. Honestly, I did not think that he would get into the PhD program. Again, Ali surprised and took the unconventional path. He become the first WES MAS student to be placed into the PhD program. To date, he is still one of only two WES MAS students to go on to a PhD (and the only one to finish the PhD).

Ali is an amazing educator. He played an integral role in the development of much of the core material of the WES MAS program. He made substantial contributions to the curriculum in my HLS class, but also other embedded classes. He TA’ed almost his entire PhD career, mostly because the program would not have survived without him.

Ali is an outstanding system builder. His work always had an applied aspect. He was a magician at getting the FPGA tools to work and building complete systems. During his PhD, he worked at Cognex and Xilinx to develop cutting edge technologies used in real-world scenarios.

Finally, and not to be overlooked, Ali is a stellar researcher. His PhD research made fundamental advances in hardware accelerated systems for spiking neural networks and for reshaping deep neural networks for implementation on FPGAs. This research was motivated by his time at Xilinx Research Labs where he spent the last 6 months of his PhD. This experience put a focus on Ali’s thesis while allowing him to continue to work on important and industrially relevant research problems. And it got him a full-time job after graduation.

I’ve learned a few things about Ali. First, never judge a book by its cover. Can a telecommunications engineer at a prison get a PhD? Ali showed it is possible. Second, never bet against Ali. You will likely lose this bet. Third, unconventional routes may not be the fastest routes, but they are often the most rewarding.

Congrats Dr. Khodamoradi!

Jeremy Blackstone: Mountaineer, UCSD CSE PhD, and Howard Professor

Congratulations to Jeremy Blackstone for successfully defending his PhD thesis! Jeremy’s PhD research focused on mitigating hardware side channels – a powerful class of security vulnerabilities that exploits the side effects of physically performing a computation. Jeremy’s research focused on the idea of “blinking”, which determines when to turn on/off side channel attack mitigation strategies. The goal is to use the mitigations during the most important time periods and turn them off during less vulnerable times in order to make the system more efficient. This provides the ability to tradeoff between security, performance, power consumption, and other important objectives.

Jeremy has been associated with our research group for a long time. He was a member of our first Engineers for Exploration Summer REU program in Summer 2013 when he was an undergraduate at Howard University. The following summer, he came to UCSD again and this time working with Dustin Richmond on the Tinker project. He was funded to participate in the summer research programs as part of the UCSD Howard Partnership for Graduate Success — a UC HBCU-funded initiative led by Profs. Gentry Patrick in Biological Sciences and Gary Cottrell in Computer Science and Engineering. These two summer research experiences were the key factor in recruiting Jeremy to UCSD. Jeremy would have otherwise not been interested in UCSD without spending the summer in San Diego. And I would have not gotten to know Jeremy and would have been less likely to consider his application and give him an offer.

Jeremy started his his PhD in 2015. During our group retreat Fall 2015, we did a challenging group hike in Mammoth Lakes scrambling up boulders for hundreds of meters near the Crystal Crag. The group picture was taken at the top of that scramble. Jeremy was not an experienced hiker and I did a very poor job of warning him (and others in the group) about the challenges of the hike. It may be hard to tell, but Jeremy was not very happy in this picture (or generally during the hike). In a lot of ways this summarizes a PhD journey. You don’t really know what you are getting into, it is very difficult, sometimes your advisor fails to warn you of pending challenges, but when you make it, you have done things that have never been done before.

Jeremy eventually recovered from that hike, and settled in on hardware security as a PhD topic. He worked with many different people and different topics over his PhD career. His published extensively with people within our group (e.g., Wei Hu, Alric Althoff, Dustin Richmond), at the University of Washington (Michael Taylor, Dustin Richmond), and at Purdue (Shreyas Sen, Debayan Das). Jeremy is clearly a multidisciplinary and collaborative researcher.

After graduation, Jeremy started as an assistant professor in the Department of Electrical Engineering and Computer Science at Howard University. Jeremy was remotely lecturing at Howard during the final year of his PhD teaching an introduction to computer science course. The professor position allows him to continue his teaching and research pursuits at his alma mater.

Congrats again Jeremy! I look forward to seeing all the mountains that you climb.


As part of an invited session “CAD for Hardware Security” at the IEEE VLSI Test Symposium (VTS), I teamed up with some giants in the hardware security space (Intel, University of Florida, and Tortuga Logic) to discuss the need for security automation tools to enable hardware security verification.

My portion of the presentation focused on the need for hardware security coverage metrics. We developed CWE-IFT that use information flow tracking (IFT) property templates based on common weakness enumerations (CWEs). This describes the current process of security verification followed at Tortuga and within our research group at UCSD.

When Rick tells you to get CWE-IFT, you better Get CWE-IFT!

And yes, CWE-IFT is pronounced “Schwifty” after the hilarious (but extremely childish and vulgar — viewer beware!) “Rick and Morty” song. This helps fulfill my childhood goals to incorporate cartoons into my job. See Mom, watching cartoons all day is a productive use of time! 🙂

To understand how to Get CWE-IFT, check out the slides and paper. I promise that they are a lot less childish and vulgar.

Paper: Sohrab Aftabjahani, Ryan Kastner, Mark Tehranipoor, Farimah Farahmandi, Jason Oberg, Anders Nordstrom, Nicole Fern, and Alric Althoff, “CAD for Hardware Security – Automation is Key to Adoption of Solutions”, IEEE VLSI Test Symposium 2021.

Slides: Ryan Kastner, Jason Oberg, Nicole Fern, and Alric Althoff, “Hardware Security Coverage“, IEEE VLSI Test Symposium 2021.

Tracking Iguanas with Drones Equipped with Software Defined Radios

Our scientific collaborators at the San Diego Zoo Wildlife Alliance have a long running research program studying the behaviors of endangered iguanas in the Caribbean. As part of their efforts to understand these animals, they attach tiny radios to the iguanas and attempt to track them over weeks to months. In the past, this has largely relied on humans equipped with directional antennas traversing rough terrain to find these radios and the iguanas attached to them.

Our Engineers for Exploration researchers felt we could do better. Over the years, we have developed a drone equipped with a software defined radio to fly over an area and find the animals. The software defined radio “listens” for the radios attached to the iguanas, and captures characteristics of each radio’s signal. We have developed automated algorithms that analyze the received data from the drone’s radio to provide an estimate about the location of the iguanas. The algorithm fuses together position estimates from different times and locations. Our field deployments over that past several years have shown that our drone-based system can effectively find radio-tagged animals.

This research was recently published in the Journal of Field Robotics. For more details, please see our paper below. Congrats to all the authors!

Nathan T. Hu, Eric K. Lo, Jen B. Moss, Glenn P. Gerber, Mark E. Welch, Ryan Kastner, and Curt Schurgers, “A More Precise Way to Localize Animals Using Drones“, Journal of Field Robotics, 2021 (pdf)

S2N2: A FPGA Accelerator for Streaming Spiking Neural Networks

Spiking Neural Networks (SNNs) utilize an event-based representation to perform more efficient computation than existing artificial neural networks. SNNs show a lot of promise for low energy computation, but are still limited by the lack of quality training tools and efficient hardware implementations.

Our recent work published at the ACM/IEEE International Symposium of Field-Programmable Gate Arrays (ISFPGA) extends the Xilinx FINN architecture to support streaming spiking neural networks (S2N2). S2N2 efficiently supports both axonal and synaptic delays for feedforward networks with interlayer connections. We show that because of the spikes’ binary nature, a binary tensor can be used for addressing the input events of a layer. We show that S2N2 works well for automatic modulation classification — an important problem for modern wireless networks.

The work was done in collaboration with Xilinx. For more details, check out Ali’s talk at ISFPGA

Paper Reference: Alireza Khodamoradi, Kristof Denolf, and Ryan Kastner, “S2N2: A FPGA Accelerator for Streaming Spiking Neural Network“, International Symposium on Field-Programmable Gate Arrays (ISFPGA) (pdf)

Two New(ish) Group Members

An extremely belated but enthusiastic welcome Olivia Weng and Jennifer Switzer — two PhD students that joined our group in Fall 2020.

Olivia Weng joins us from the University of Chicago where she got her BS in Computer Science. As an undergraduate, her research with Prof. Andrew Chien (formerly a UCSD professor) studied the use of machine learning techniques to optimize operating system requests.

Jennifer Switzer got an MEng and BS from MIT. Her Masters thesis looked at vulnerabilities that arise when “safe” processes written in Rust interact in potentially unsafe manners through inter-process communication.

Welcome Liv and Jen!

Distinguished Lecture & Tutorial on Property Driven Hardware Security

December 2020 involved a couple of major events related to our hardware security research — a HOST Tutorial and a CASA Distinguished Lecture. Ryan and Dr. Nicole Fern from Tortuga Logic gave a tutorial at IEEE International Symposium on Hardware Oriented Security and Trust (HOST) HOST 2020. Ryan was also invited to give a Distinguished Lecture in the CASA Cluster of Excellence at Ruhr University Bochum. Both events focused on our work on Property Driven Hardware Security.

Property driven hardware security is a design methodology to assess the safety and security of hardware designs. It enables security experts to describe how the hardware should (or should not) function. These security properties are formally specified using languages that map to models that are easy to verify using existing design tools. There are three fundamental elements for any hardware security design flow. First, security experts need expressive languages to specify these security properties. Second, these properties should map to models to describe the security related behavior of a hardware design. Finally, hardware security design tools verify that the hardware design meets these properties using formal solvers, simulation, and emulation.

The HOST tutorial was one of six selected to provide HOST attendees with an in-depth look at important topics in hardware security. I gave a similar tutorial in the last HOST that was well-received and invited back for another year. This time around, the tutorial included Dr. Nicole Fern from Tortuga Logic. Nicole provided a great presentation on the types of properties that modern hardware security verification tools can handle. I added an in-depth look about how these tools can verify security properties. Have a look yourself at the materials made available to the attendees if you would like.

The Distinguished Lecture was a great honor for me. I really admire the research done in CASA Cluster of Excellence — they have an outstanding group of researchers that I have followed for many years (even decades). This invitation did lead me to consider what one needs to do in order to be eligible to give a distinguished lecture. My conclusion is that one mostly just needs to be a researcher for a long enough time and then their work becomes distinguished. And that made me feel a bit old. So before my talk I made sure to shave and pluck out grey hairs. The folks at CASA did a nice job of producing a video of the talk:

X-Ray Vision: Enhancing Liver Surgery with Augmented Reality

Liver cancer has the fastest growth of incidence and the second highest mortality of all cancers in the United States. Worldwide, it is estimated that over one million people will die from liver cancer in 2030. Liver resection (hepatectomy) is the paradigm for treating liver cancer. A crucial part of a partial hepatectomy is understanding where the tumors, vessels, and other important landmarks are located. To aid in this, the patient typically undergoes preoperative cross-sectional imaging (e.g., CT/MR scans). Surgeons use these images to determine resectability based upon the location of important structures (e.g., veins), analyze tumor margins, accurately compute future liver remnant volumes, and generally aid in surgical planning and navigation.

An augmented reality image guidance system for enhancing liver surgery.

However, it is challenging for the surgeon to mentally register preoperative cross-sectional images to the surface of the liver at the time of operation since surgical actions cause significant and sometimes permanent liver deformations that lead to mismatches with cross-sectional images. Mentally integrating preoperative data into the operative field is time consuming and error prone. This can make it difficult to accurately localize smaller tumors intra-operatively, which can affect surgical decision making and adequate resection of primary and metastatic liver tumors.

Dr. Michael Barrow‘s PhD thesis developed augmented Reality (AR) image guidance techniques that merge preoperative data directly into the surgeons view during surgery. The goal is to provide surgeons with what Michael describes as “X-ray vision” — allowing them to see through tissues and better understand where blood vessels, tumors, and other important surgical landmarks lie.

Current scenario: The surgeon has to estimate internal vessel positions
X-Ray vision: the surgeon is presented an AR overlay of internal landmarks.

The research brings together many state-of-the-art technologies. It requires computer vision approaches to track the surgical scene, real-time mechanical modeling of the organ to accurately place the important unseen surgical landmarks, augmented reality to visualize the landmarks, and hardware accelerated compute systems to process the high throughput sensor data. He showed that patient specific biomechanical modeling results in clinically significant increases in accuracy. Specifically, he built a system that uses magnetic resonance elastography to create a patient-specific mechanical model. The system works in real-time to provide accurate positions of unknown landmarks. He physically validated the techniques by creating a phantom mechanical platform to demonstrate it is possible to track landmarks internal to the phantom liver.

Left: Overview of the complete AR surgical system. Right: Experimental platform used to validate the AR accuracy

Michael took an unconventional path to his PhD. Unlike most PhDs, he laid out his research topic almost solely on his own. He spent a lot of time shadowing medical doctors to understand their problems. He deftly maneuvered through many different fields, seeking out and finding key collaborators. The result is an amazing example of an interdisciplinary thesis that has tremendous potential value in a clinical setting.

Michael developed a number of other technologies that are not reflected in his thesis. Most recently he is focusing on developing technologies to help into COVID-19 crisis which was awarded an UCSD Institute of Engineering in Medicine Galvanizing Engineering in Medicine award. He lead a team of undergraduates to build systems to better scale the care of COVID-19 patients (for more information see CSE Research Highlight).

Michael was a real tour de force in pushing collaborations between the School of Engineering and the School of Medicine. In addition to his Phd thesis project, he developed a close collaboration with Dr. Shanglei Liu and made many other connections between our research group and the medical school that will certainly create more future fruitful collaborations.

After graduation, Michael started a post-doctoral position at Lawrence Livermore National Labs.

Ancient China from Above

Our large-scale 3D modeling work was featured on the National Geographic Docuseries “Ancient China from Above“. We developed 3D models using drones, multispectral cameras, lidar, and other cutting edge technology, which provided archaeologist Alan Maca new insights to better understand ancient Chinese civilizations.

As part of the production, Ryan and Eric Lo traveled to some of the most remote parts of China including Xanadu (Kublai Khan’s summer palace in Inner Mongolia), the Han Great Wall in the Gobi Desert, and Shimao — a new archaeological site known as China’s Pompeii located on the Loess plateau.

The three part series aired on the National Geographic Channel and is available on most video streaming platforms. The full “Secrets of the Great Wall” episode is available on YouTube. We appear around the 26 minute mark.