I study censorship and network security, and my work seeks to enable open communication and support missions in cyberspace. I earned my Ph.D. in Computer Science at the University of Maryland, advised by Dave Levin.
I created Geneva, a genetic algorithm that discovers ways to evade nation-state Internet censorship, and advise the censorship team in the Breakerspace Lab. I am honored to be a winner of Facebook and USENIX’s Internet Defense Prize, IRTF’s Applied Network Research Prize (ANRP) in 2020 and 2024, a recipient of USENIX Security’s Distinguished Paper Award, FOCI’s Best Practical Paper, CSAW’s Applied Research Competition Winner, and ACM SIGCOMM’s Doctoral Dissertation Award Winner.
Outside of my censorship work, I am currently working with Amazon Web Services and with the University of Maryland as an adjunct faculty member. I am the creator of HACS408T: Introduction to Penetration Testing for the University of Maryland Honors College Program ACES (Advanced Cybersecurity Experience for Students), which I teach every Spring semester.
PhD in Computer Science, 2022
University of Maryland
Masters in Computer Science, 2018
University of Maryland
BS in Computer Science, 2017
University of Maryland
We present the first global study of connection tampering through a passive analysis of traffic received at a global CDN, Cloudflare. Our study shows that passive measurement can be a powerful complement to active measurement in understanding connection tampering and improving transparency.
In this paper, we measure and characterize the GFW’s new system for censoring fully encrypted traffic. We find that, instead of directly defining what fully encrypted traffic is, the censor applies crude but efficient heuristics to exempt traffic that is unlikely to be fully encrypted traffic; it then blocks the remaining non-exempted traffic. Our understanding of the GFW’s new censorship mechanism helps us derive several practical circumvention strategies. We responsibly disclosed our findings and suggestions to the developers of different anti-censorship tools, helping millions of users successfully evade this new form of blocking.
Since 2006, Turkmenistan has been listed as one of the few Internet enemies by Reporters without Borders due to its extensively censored Internet and strictly regulated information control policies, but it is difficult to study due to its small population and low internet penetration rate. In this paper, we present the largest measurement study to date of Turkmenistan’s Web censorship. We apply our tool TMC to 15.5M domains, our results reveal that Turkmenistan censors more than 122K domains, using different blocklists for each protocol. We also reverse-engineer these censored domains, identifying 6K over-blocking rules causing incidental filtering of more than 5.4M domains.
In this paper, we present the first techniques to automate the discovery of new censorship evasion techniques purely in the application layer. We present a general solution and apply it specifically to HTTP and DNS censorship in China, India, and Kazakhstan. Our automated techniques discovered a total of 77 unique evasion strategies for HTTP and 9 for DNS, all of which require only application-layer modifications, making them easier to incorporate into apps and deploy.
In this paper, we present evidence that suggests the GFW has deployed a second HTTPS censorship middlebox that runs in parallel to the first. We present a detailed analysis of this secondary censorship middlebox—how it operates, the content it blocks, and how it interacts with the primary middlebox. We also present several packet-based evasion strategies for the secondary middlebox and demonstrate that the primary censorship middlebox can be defeated independently from the secondary.
In this paper, we present the first non-trivial TCP-based DDoS amplification attack by weaponizing censoring middleboxes. We develop a novel mechanism to discover these amplification attacks and perform Internet-wide measurements to measure the threat censoring middleboxes pose. We find hundreds of thousands of IP addresses that offer amplification factors greater than 100×. We also report on network phenomena that causes some of the TCP-based attacks to be so effective as to technically have infinite amplification factor (after the attacker sends a constant number of bytes, the reflector generates traffic indefinitely).
Censors pose an even greater threat to the Internet than previously understood. We demonstrate an off-path attack that exploits residual censorship, a feature by which a censor continues blocking traffic between two end-hosts for some time after a censorship event. Our attack sends spoofed packets with censored content, keeping two victim end-hosts separated by a censor from being able to communicate with one another. This attack allows anyone to weaponize censorship infrastructure to perform their own blocking.
Earlier this year, Iran deployed their protocol filter that permits only a small set of protocols (DNS, HTTP, and HTTPS) and censors connections using any other protocol. In this paper, we present the first detailed analysis of Iran’s protocol filter: how it works, its limitations, and how it can be defeated.
In this paper, we present the first purely server-side censorship evasion strategies—11 in total—enabling servers to subvert censorship on behalf of clients. We extend Geneva to automate the discovery and implementation of server-side strategies, and we apply it to four countries (China, India, Iran, and Kazakhstan) and five protocols (DNS-over-TCP, FTP, HTTP, HTTPS, and SMTP).
In this paper, we present the first purely server-side censorship evasion strategies—11 in total—enabling servers to subvert censorship on behalf of clients. We extend Geneva to automate the discovery and implementation of server-side strategies, and we apply it to four countries (China, India, Iran, and Kazakhstan) and five protocols (DNS-over-TCP, FTP, HTTP, HTTPS, and SMTP).
We present Geneva, a novel genetic algorithm that evolves packet-manipulation-based censorship evasion strategies against nation-state level censors. With experiments performed both in-lab and against several real censors (in China, India, and Kazakhstan), we demonstrate that Geneva is able to quickly and independently re-derive most strategies from prior work, and derive novel subspecies and altogether new species of packet manipulation strategies.