About Me

Howdy! I’m currently a 3rd-year Computer Science Ph.D. candidate at University of California, Riverside (UCR). My advisor is Prof Zhiyun Qian.

News

Jun/2019: Joined Samsung Research America (SRA) as a research intern.
May/2019: Invited to present our work at Mozilla Security Research Summit 2019 [video].
May/2019: Our paper on ML/graph-based adblocking accepted at IEEE S&P 2020.
May/2019: Presented ShadowBlock at WWW 2019.
Jan/2019: Paper accepted at WWW 2019.
May/2018: Manuscript posted on arXiv.
Feb/2018: Presented our work at NDSS 2018 in San Diego.
Jan/2018: Our anti-adblocking research covered by [TechCrunch] [Arcs Technica]
Dec/2017: Invited to present our work at Data Transparency Lab Conference as a grantee in Barcelona. Thanks DTL!
Oct/2017: Paper accepted at NDSS 2018.
Sep/2016: Started Ph.D. at University of California, Riverside.
Jul/2016: Graduated from CQUPT with Honors.
Jan/2016: Joined Deloitte TTL as a consulting intern.
Jul/2015: Joined Douban Inc. as a software engineering intern.

Research Interest

I’m broadly interested in computer security and web privacy. My current research focuses on privacy-enhancing technologies. Nowadays, the popularity of online advertisements has made them an attractive vector for various types of abuses. I’m working on improving the effectiveness of adblocking by (i) measuring/analyzing the escalating arms race between adblockers and anti-adblockers through program analysis; (ii) making adblockers stealthy against anti-adblockers via browser modifications; and (iii) leveraging machine learning to better identify advertising- and tracking-related resources.

Recently, I’ve also started to explore adversarial machine learning (e.g. adversarial example, Generative Adversarial Network (GAN)), and their applications in security and privacy research.

Publications

  1. AdGraph: A Graph-Based Approach to Ad and Tracker Blocking [arVix ver.][code]
    Umar Iqbal, Peter Snyder, Shitong Zhu, Benjamin Livshits, Zhiyun Qian and Zubair Shafiq
    To appear in the Proceedings of the IEEE Symposium on Security & Privacy (S&P), May 2020
  2. ShadowBlock: A Lightweight and Stealthy Adblocking Browser [paper][code][demo]
    Shitong Zhu, Umar Iqbal, Zhongjie Wang, Zhiyun Qian, Zubair Shafiq and Weiteng Chen
    The Web Conference (WWW), San Francisco, CA, May 2019
  3. Measuring and Disrupting Anti-Adblockers Using Differential Execution Analysis [paper][slides][video][code]
    Shitong Zhu, Xunchao Hu, Zhiyun Qian, Zubair Shafiq and Heng Yin
    The Network and Distributed System Security Symposium (NDSS), San Diego, CA, Feb 2018
  4. On Selecting Composite Network-Cloud Services: A Quality-of-Service Based Approach [paper]
    Minkailu Mohamed Jalloh, Shitong Zhu, Fang Fang and Jun Huang
    International Conference on Research in Adaptive and Convergent Systems (RACS), Prague, Czechia, Oct 2015
  5. A Source-location Privacy Protection Strategy via Pseudo Normal Distribution-based Phantom Routing in WSNs [paper]
    Jun Huang, Meisong Sun, Shitong Zhu, Yi Sun, Cong-cong Xing and Qiang Duan
    The 30th Annual ACM Symposium on Applied Computing (SAC), Salamanca, Spain, April 2015
  6. A Defense Model of Reactive Worms Based on Dynamic Time [paper]
    Haokun Tang, Shitong Zhu, Jun Huang and Hong Liu
    Journal of Software, Nov 2014
  7. Propagation of Active Worms in P2P Networks: Modeling and Analysis [paper]
    Haokun Tang, Yukui Lu, Shitong Zhu and Jun Huang
    Journal of Computers, Nov 2014

Posters

  1. ShadowBlock: A Lightweight and Stealthy Adblocking Browser [poster]
    Shitong Zhu, Umar Iqbal, Zhongjie Wang, Zhiyun Qian, Zubair Shafiq and Weiteng Chen
    Midwest Security Workshop, Chicago, IL, April 2019

Talks

  1. Arms Race between Adblockers and Anti-adblockers [video]
    Mozilla Security Research Summit, San Francisco, CA, May 2019
  2. Detection and Circumvention of Ad-Block Detectors [video]
    Data Transparency Lab Conference, Barcelona, Spain, Dec 2017

Work Experience


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