I build real systems and new tools to improve end user privacy using every tool possible from Systems, Cryptography, and Programming Languages.

I'm working on creating tools and systems to help developers ensure their applications comply with desired privacy policies. I built Sesame, a practical end-to-end privacy enforcement system for Rust applications. Sesame draws inspiration from earlier work on IFC. However, Sesame relies on the guarantees of the Rust type system, and a new design centered around small, isolated privacy regions, to achieve enforcement more efficiently and with less developer burden. I'll be presenting our paper describing Sesame at SOSP 2024, but you can sneak-a-peak at a preprint here.  

I am interested in achieving compliance-by-construction for privacy legislation via drop-in systems. I built K9db, a database with per-user physical storage. K9db has a MySQL-like API and can be used by web applications with only a few schema annotations. K9db provides  correct-by-construction endpoints for complying with GDPR subject access requests and encryption at rest with per-user keys, with at-most a modest overhead compared to non-compliant databases. K9db appeared in OSDI 2023!

I designed and built DP-PIR,  a novel cryptographic protocol and system for Private Information Retrieval, which allows users to query a remotely-held database privately, without revealing the content of their queries to the service. DP-PIR combines ideas from Cryptographic Secret Sharing, Mixnets and anonymous network systems, and differential privacy  (among others). This allows it to achieve constant computation and communication complexity for servers and clients, and concrete speedups over two orders of magnitude, for applications with high query rates. With DP-PIR, loads and applications previously believed to be impractical, such as mobile app updates, contact tracing, dependency vulnerability detection, map routing, and many others, can now be carried out privately. This work appeared in USENIX Security 2022.

I built various open-source software packages for secure computation, worked on associated developer tool-chains, and studied and improved the usability of secure computation. My work has been deployed in the real-world to measure the wage gap in the greater Boston area privately, in collaboration with the Boston Women Workforce Council and the Greater Boston Chamber of Commerce, with recent deployments handling data from over 100 Boston companies representing billions of dollars in wages, and over 16% of the greater Boston workforce.  My work, along with many of my collaborators, led to the formation of a secure computation startup, nthparty, and was cited in the White House’s National Strategy to Advance Privacy Preserving Data Sharing and Analytics, the UN Handbook on Privacy-Preserving Computation Techniques, and the European Commission's report on Technological Enablers for Privacy  Preserving Data Sharing and Analysis.

I am advised by Malte Schwarzkopf. Before joining Brown, I received a masters in Computer Science from Boston University in 2020, and a bachelors in Computer Science from the American University of Beirut (AUB) in 2015.  I was a senior software engineer at InteractiveLife, and a software engineering fellow at the Software and Application Innovation Lab (SAIL). I was a visiting student at MIT with Professor Dina Katabi and the Emerald Innovation team.  I interned at Google with the NetInfra team.

Sesame: Practical End-to-End Privacy Compliance with Policy Containers and Privacy Regions
Kinan Dak Albab, Artem Agvanian, Allen Aby, Corinn Tiffany, Alexander Portland, Sarah Ridley, Malte Schwarzkopf
SOSP 2024
Preprint Version

K9db: Privacy-Compliant Storage For Web Applications By Construction
Kinan Dak Albab, Ishan Sharma, Justus Adam, Benjamin Kilimnik, Aaron Jeyaraj, Raj Paul, Artem Agvanian, Leonhard Spiegelberg, Malte Schwarzkopf
OSDI 2023
Published Version

Batched Differentially Private Information Retrieval
Kinan Dak Albab, Rawane Issa, Mayank Varia, Kalman Graffi
USENIX Security 2022
Published Version | Extended Version on eprint

SwitchV: Automated SDN Switch Validation with P4 Models
Kinan Dak Albab, Jonathan DiLorenzo, Stefan Heule, Ali  Kheradmand, Steffen Smolka, Konstantin Weitz, Muhammad Tirmarzi, Jiaqi Gao, Minlan Yu
SIGCOMM 2022
Published Version

Tutorial: Deploying Secure Multi-Party Computation on the Web Using JIFF
Kinan Dak Albab, Rawane Issa, Andrei Lapets, Peter Flockhart, Lucy Qin, Ira Globus-Harris
SecDev 2019
Published Version

From Usability to Secure Computing and Back Again
Lucy Qin, Andrei Lapets, Frederick Jansen, Peter Flockhart, Kinan Dak Albab, Ira Globus-Harris, Shannon Roberts, Mayank Varia
USENIX SOUPS 2019
Published version

Accessible Privacy-Preserving Web-Based Data Analysis for Assessing and Addressing Economic Inequalities
Andrei Lapets, Frederick Jansen, Kinan Dak Albab, Rawane Issa, Lucy Qin, Mayank Varia, Azer Bestavros
ACM COMPASS 2018
Published version

Model and Program Repair via SAT Solving
Paul C. Attie, Kinan Dak Al Bab, and Mohamad Sakr
ACM Transactions on Embedded Computing Systems (TECS) 2017.
Published version

Full list on Google scholar!

• CSCI 2390: Privacy-Conscious Systems (Fall 2024). Instructor of Record.

• Summer@Brown's Introduction to Computer Science with the Rust Programming Language (Summer 2024). Instructor and designer.

• CSCI 2390: Privacy-Conscious Systems (Fall 2023, 2021): Teaching assistant with Prof. Malte Schwarzkopf. Brown University.

• CS 591 L1: Embedded Languages and Frameworks (Fall 2019). Instructor of Record.

• CS 591 K1: Foundations and Pragmatics of Dependently-Typed Automated Systems (Spring 2019).  Co-designer and Co-instructor with Prof. Assaf Kfoury.

• Computer Science Summer Challenge (Summer 2017, Summer 2018). Intensive CS summer program for rising high school students. Instructor and designer.

• Teaching Assistant for Theory of Computation, Operating Systems, Discrete Mathematics for various semesters at Boston University and the American University of Beirut.

• Teaching Excellence Award: Boston University, Department of Computer Science, 2020.

• Vivli and Microsoft datatheon on Privacy and Utility of Rare Diseases Datasets: Outstanding Graduate Submission, 2019.

• Hariri Institute for Computing (HIC @ BU) Gradute Student Fellow 2017-2020.

• Mark Sawaya Excellence Award , Best Graduating Student in Computer Science (AUB), 2015.

• AUB Dean's Honor List: Fall 2013, Spring 2014.

• 1st Place in ACM Lebanese Collegiate Programming Contest (Team Khawarizmi), 2015.

• 1st Place in AUB's Supernacci Math Programming Competition (Team 0xdeadbeef), 2015. 

Big fan of modern C++, move semantics, and templates.

Coq hobbyist: my shower thoughts often drift to thinking up scenarios for theorem assistants and privacy. Drop me a line if you have related ideas or want to collaborate.

When I am not on my Computer, I am probably at a Metal show, grilling in the backyard, or drinking some beer.

If you are reading this, go listen to Lorna Shore, or better yet, listen to my bad guitar playing in my very own doom metal band from way back in high school!

Let's go Red Sox! Yankees suck.