Hieu Le

PhD Student

University of California, Irvine

Hieu Le

I am a 5th year PhD student in Electrical Engineering and Computer Science (EECS) at UC Irvine. I am advised by Athina Markopoulou and part of the ProperData NSF Frontier project. My research lies at the intersection of privacy and networking to improve (1) transparency of data collection practices by characterizing advertising and tracking ecosystems across different platforms such as the web, smart TVs and Oculus VR; and (2) control of data collection by designing frameworks and methodologies to automate the pain-points of privacy-enhancing technologies (PETs) that block advertising and tracking on the web. For more information, see my CV.

Latest 2023 News:

I will be presenting AutoFR at USENIX Security 2023. Its code and dataset received all USENIX artifact badges for Available, Functional, and Reproduced.
I am honored to receive the Graduate Dean’s Dissertation Fellowship 2023.
I will be attending IEEE S&P 2023 from May 22-25rd as a Student Travel Grant Recipient.
I was an invited panelist at the Electrical Engineering Specialization Panel, hosted by IEEE.

Interests

Ads & Tracking Ecosystems
Filter Rule Generation
Network Measurements
Framework/System Design

Education

PhD in Computer Engineering, 2018-Current
University of California, Irvine
M.S., Computer Engineering, 2021
University of California, Irvine - GPA 3.96
B.S., Computer Science and Engineering, 2009
University of California, Irvine - GPA 3.6

Publications

Hieu Le, Salma Elmalaki, Athina Markopoulou, Zubair Shafiq (2022). AutoFR: Automated Filter Rule Generation for Adblocking. USENIX Conference on Security Symposium (SEC) 2023.

PDF Code Dataset Project Extended Paper Talk (2022) Talk (2021)

Rahmadi Trimananda, Hieu Le, Hao Cui, Janice Ho, Anastasia Shuba, Athina Markopoulou (2021). OVRSeen: Auditing Network Traffic and Privacy Policies in Oculus VR. USENIX Conference on Security Symposium (SEC) 2022.

PDF Project arXiv

Hieu Le, Athina Markopoulou, Zubair Shafiq (2020). CV-Inspector: Towards Automating Detection of Adblock Circumvention. NDSS 2021.

PDF Code Dataset Project Amazon Machine Image NDSS 2021 Video

Janus Varmarken, Hieu Le, Anastasia Shuba, Athina Markopoulou, Zubair Shafiq (2020). The TV is Smart and Full of Trackers: Measuring Smart TV Advertising and Tracking. In PoPETs 2020, Issue 2, (Janus and Hieu are co-first authors).

PDF Dataset Project Video DOI Firetastic Code Rokustic Code PrivacyCon2021

Anastasia Shuba, Evita Bakopoulou, Milad Asgari Mehrabadi, Hieu Le, David Choffnes, Athina Markopoulou (2018). Antshield: On-device detection of personal information exposure. arXiv:1803.01261.

See all publications

News

AutoFR: Automated Filter Rule Generation for Adblocking has been accepted to USENIX Security 2023!

Congrats to all co-authors!

Hieu Le, Salma Elmalaki, Athina Markopoulou, Zubair Shafiq

Last updated on Nov 18, 2022 1 min read Publication

AutoFR: Automated Filter Rule Generation for Adblocking has been accepted to USENIX Security 2023!

OVRSeen at PrivacyCon 2022 (hosted by FTC)

Rahmadi Trimananda, is presenting our USENIX 2022 paper on Auditing Network Traffic and Privacy Policies at PrivacyCon 2022.

Rahmadi Trimananda, Hieu Le, Hao Cui, Janice Ho, Anastasia Shuba, Athina Markopoulou

Last updated on Sep 30, 2022 1 min read Presentation

OVRSeen at PrivacyCon 2022 (hosted by FTC)

OVRSeen: Auditing Network Traffic and Privacy Policies in Oculus VR has been accepted to USENIX Security 2022!

Our work, OVRSeen: Auditing Network Traffic and Privacy Policies in Oculus VR, lead by Rahmadi Trimananda, been accepted to USENIX Security 2022.

Rahmadi Trimananda, Hieu Le, Hao Cui, Janice Ho, Anastasia Shuba, Athina Markopoulou

Last updated on Oct 3, 2021 1 min read Publication

OVRSeen: Auditing Network Traffic and Privacy Policies in Oculus VR has been accepted to USENIX Security 2022!

Recent & Upcoming Talks

AutoFR: Automated Filter Rule Generation for Adblocking

The talk presents our work on AutoFR for filter rule rule generation. We will walk through the formulation, implementation and evaluation of AutoFR.

Sep 27, 2022 Amsterdam, Netherlands

Slides Video Ad-Filtering Dev Summit 2022

AutoFR: Automated Filter Rule Generation for Adblocking

Towards Automatic Generating and Testing of Filter Rules

The talk discusses how we can model the problem of filter rule generation as a reinforcement learning problem. We implement our RL framework and reveal some preliminary results.

Oct 20, 2021 Virtual

Towards Automatic Generating and Testing of Filter Rules

Revisiting Adblock Circumvention

The talk discusses the differences between different circumvention techniques (cloaking vs. obfuscation techniques). It will go over the state of anti-circumvention and how our work can help reduce human labeling effort to identify sites with successful circumvention.

Oct 21, 2020 — Virtual

Revisiting Adblock Circumvention

Measuring and Mitigating Adblock Circumvention in the Wild

After an overview of different circumvention techniques, this talk will describe an ML approach to automatically detect circumvention in the wild as well as identify popular third-party circumvention providers.

Sep 27, 2019 — Amsterdam, Netherlands

Measuring and Mitigating Adblock Circumvention in the Wild

Skills

Python

JavaScript

HTML

CSS

Chrome Extensions

Amazon Web Services

Docker

Java

Android