About Me

Howdy! I’m currently a 4th-year Computer Science Ph.D. candidate at University of California, Riverside (UCR). My advisor is Prof Zhiyun Qian.

News

Sep/2020: Our paper on leveraging context learning to thwart DPI evasion attacks conditionally accepted at CoNEXT 2020.
Jul/2020: Our paper on leveraging context consistency to detect adversarial perturbations for object detectors accepted at ECCV 2020.
Apr/2020: Received the Dissertation Year Program (DYP) Award. Thanks UCR!
Jan/2020: Manuscript posted on arXiv.
Jan/2020: Joined Samsung Research America (SRA) again as a research intern.
Dec/2019: Our paper on eluding stateful DPI systems is conditionally accepted at NDSS 2020.
Dec/2019: Invited to give a talk at XJTU InForSec event in Xi’an, China.
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.

Pre-prints

  1. A4: Evading Learning-based Adblockers [manuscript]
    Shitong Zhu, Zhongjie Wang, Xun Chen, Shasha Li, Umar Iqbal, Zhiyun Qian, Kevin S Chan, Srikanth V Krishnamurthy and Zubair Shafiq
    arXiv preprint arXiv:2001.10999

Publications

  1. You Do (Not) Belong Here: Detecting DPI Evasion Attacks with Context Learning [paper][code]
    Shitong Zhu, Shasha Li, Zhongjie Wang, Xun Chen, Zhiyun Qian, Srikanth V. Krishnamurthy, Kevin S. Chan, Ananthram Swami
    To appear in Conference on emerging Networking EXperiments and Technologies (CoNEXT), Virtual, Dec 2020
  2. Connecting the Dots: Detecting Adversarial Perturbations Using Context Inconsistency [paper]
    Shasha Li, Shitong Zhu, Sudipta Paul, Amit Roy-chowdhury, Chengyu Song, Srikanth Krishnamurthy, Ananthram Swami, Kevin S Chan
    European Conference on Computer Vision (ECCV), Virtual, Aug 2020
  3. AdGraph: A Graph-Based Approach to Ad and Tracker Blocking [paper][code]
    Umar Iqbal, Peter Snyder, Shitong Zhu, Benjamin Livshits, Zhiyun Qian and Zubair Shafiq
    IEEE Symposium on Security & Privacy (S&P), Virtual, May 2020
  4. SymTCP: Eluding Stateful Deep Packet Inspection with Automated Discrepancy Discovery [paper][code]
    Zhongjie Wang, Shitong Zhu, Yue Cao, Zhiyun Qian, Chengyu Song, Srikanth Krishnamurthy, Tracy D. Braun and Kevin S. Chan
    Network & Distributed System Security Symposium (NDSS), San Diego, CA, Feb 2020
  5. 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
  6. 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 & Distributed System Security Symposium (NDSS), San Diego, CA, Feb 2018
  7. 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
  8. 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
  9. 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
  10. 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. Adblocking: A Slient Online Arms Race
    XJTU InForSec Event, Xi’an, China, Dec 2019
  2. Arms Race between Adblockers and Anti-adblockers [video]
    Mozilla Security Research Summit, San Francisco, CA, May 2019
  3. Detection and Circumvention of Ad-Block Detectors [video]
    Data Transparency Lab Conference, Barcelona, Spain, Dec 2017

Work Experience

Professional Services


Powered by Jekyll