Archive for the 'Privacy' Category

Aggregating Private Sparse Learning Models Using Multi-Party Computation

Friday, December 9th, 2016

Bargav Jayaraman presented on privacy-preserving sparse learning at the Private Multi‑Party Machine Learning workshop attached to NIPS 2016 in Barcelona.

A short paper summarizing the work is: Lu Tian, Bargav Jayaraman, Quanquan Gu, and David Evans. Aggregating Private Sparse Learning Models Using Multi-Party Computation [PDF, 6 pages].

At the workshop, Jack Doerner also presented a talk on An Introduction to Practical Multiparty Computation.

Secure Stable Matching at Scale

Tuesday, August 30th, 2016

Our paper on secure stable matching is now available [PDF, 12 pages]:

Jack Doerner, David Evans, abhi shelat. Secure Stable Matching at Scale. 23rd ACM Conference on Computer and Communications Security (CCS). Vienna, Austria. 24-28 October 2016.

See the site for the code and data. Jack Doerner will present the paper at CCS in October.


When a group of individuals and organizations wish to compute a stable matching — for example, when medical students are matched to medical residency programs — they often outsource the computation to a trusted arbiter to preserve the privacy of participants’ preference rankings. Secure multi-party computation presents an alternative that offers the possibility of private matching processes that do not rely on any common trusted third party. However, stable matching algorithms are computationally intensive and involve complex data-dependent memory access patterns, so they have previously been considered infeasible for execution in a secure multiparty context on non-trivial inputs.

We adapt the classic Gale-Shapley algorithm for use in such a context, and show experimentally that our modifications yield a lower asymptotic complexity and more than an order of magnitude in practical cost improvement over previous techniques. Our main insights are to design new oblivious data structures that exploit the properties of the matching algorithms. We then apply our secure computation techniques to the instability chaining algorithm of Roth and Peranson, currently in use by the National Resident Matching Program. The resulting algorithm is efficient enough to be useful at the scale required for matching medical residents nationwide, taking just over 17 hours to complete an execution simulating the 2016 NRMP match with more than 35,000 participants and 30,000 residency slots.

FTC Visit

Thursday, August 18th, 2016

Great to visit our former student Joseph Calandrino at the Federal Trade Commission in DC, where he is now a Research Director.

Denis Nekipelov and I gave a joint talk there about using secure multi-party computation techniques to enable data analyses across sensitive, divided data sets in the room where the FTC commissioners meet.

Denis Nekipelov, Joseph Calandrino, David Evans, Devesh Ravel

SRG at Oakland 2016

Wednesday, May 25th, 2016

At the IEEE Symposium on Security and Privacy in San Jose, CA, Samee Zahur presented on Square-Root ORAM and Anant, Jack, and Sam presented posters.

Anant Kharkar
Evading Web Malware Classifiers using Genetic Programming

Jack Doerner
Secure Gale-Shapley: Efficient Stable Matching for Multi-Party Computation

Samuel Havron
Secure Multi-Party Computation as a Tool for Privacy-Preserving Data Analysis

Apple and the FBI

Thursday, February 25th, 2016

I’m quoted in this article on the controversy over the FBI’s requests to Apple for assistance in unlocking an iPhone used by one of the San Bernardino terrorists: Unlocking Terrorist’s iPhone Won’t Risk Your Security, Discovery News, 24 February 2016.

“Backdoors are complicated and impossible technical challenges and would risk everyone’s privacy,” Evans said. “But what the FBI is asking for is different from what Apple says the FBI is asking for.”

For the most part, I think the article gets things right. It is very misleading to conflate what the FBI has asked for here with a cryptographic backdoor that would indeed dangerously risk everyone’s privacy and security. I covered some of the technical aspects of this in my introductory computing course last week.

Computer Science Grad Stands Watch for Users of Google’s Popular Browser

Tuesday, December 8th, 2015

Adrienne Porter Felt (BSCS 2008) returned to UVa last Friday as a Distinguished Alumni Speaker. UVa Today published this article:

Computer Science Grad Stands Watch for Users of Google’s Popular Browser
, UVa Today, 7 December 2015.

Adrienne Porter Felt’s job is to keep you secure on Chrome.

Felt, 29, who earned a computer science degree from the University of Virginia in 2008, leads the usable security team at Google working on the popular Internet browser.

Taking Evans’ offer for a research project was a turning point in Felt’s life, showing her something she liked that she could do well.

“It turned out that I really loved it,” she said. “I like working in privacy and security because I enjoy helping people control their digital experiences. I think of it as, ‘I’m professionally paranoid so that other people don’t need to be.’”

Karsten Nohl Interview

Monday, August 31st, 2015

Atlas Obscura has an article about Karsten Nohl (PhD 2009):
Exit Interview: I’m A Crypto-Specialist Working To Secure the Internet For A Billion People, Jeremy Berke, 28 July 2015.

One of the things we’re building is a PayPal competitor–with a modest target of having a few hundred million customers. Everything in India is always on a massive scale. If you could get rid of PayPal passwords, and instead just have a fingerprint–if you could pay for goods at a store with just your fingerprint, that would simplify people’s lives a lot. It would also have the secondary effect of saving some of the security problems, like phishing, that we currently encounter. And this government database is a huge enabler.

If we already have a mandate to collect everybody’s fingerprints, why not use it in the customer’s benefit? The privacy risk is always there. That’s the law and I can’t argue with that. But if the law is already creating this risk, why not create opportunity in the same step?

Understanding and Monitoring Embedded Web Scripts

Thursday, March 26th, 2015

Modern web applications make frequent use of third-party scripts, often in ways that allow scripts loaded from external servers to make unrestricted changes to the embedding page and access critical resources including private user information. Our paper describing tools to assist site administrators in understanding, monitoring, and restricting the behavior of third-party scripts embedded in their site, and what we’ve learned by using them, is now available: Yuchen Zhou and David Evans, Understanding and Monitoring Embedded Web Scripts, IEEE Symposium on Security and Privacy 2015.

Yuchen will present the paper at the Oakland conference (in San Jose) this May.

Project Site:

Who Does the Autopsy?

Wednesday, March 25th, 2015

This (perhaps somewhat oversensationalized) article in Slate draws from Nate Paul’s research on medical device security: If you Die after Someone Hacks Your Glucose Monitor Who Does the Autopsy? (Slate, 13 March 2015).

According to researchers at the Oak Ridge National Laboratory, in 2003 and 2009 respectively, the “Slammer” and “Conficker” worms had each successfully infected networked hospital systems responsible for monitoring heart patients. Since the days of Slammer and Conficker, malware has since become even more sophisticated, and a Trojan with a specifically engineered piece of malicious code, could cause harm to numerous patients around the world simultaneously.

While a small community of researchers, and even some government regulators, such as the FDA and FTC, have begun to pose important questions about the privacy and security implications of incorporating computer technology into biological systems, so far law enforcement and criminal justice authorities have been mostly absent from any substantive conversations.

iDash Competition Winner

Tuesday, March 17th, 2015

Congratulations to Samee Zahur for winning the iDash Secure Genomics competition (Hamming Distance challenge task), sponsored by Human Longevity, Inc. A video of the event is available at

Samee’s solution was built using Obliv-C, and the code will be posted soon.