Limin Yang   (杨利民)

I am a fifth-year Ph.D. candidate of Computer Science at UIUC.
I focus on machine learning security and explainable AI.
My advisor is Prof. Gang Wang.

I'm on the industry job market! Please email me if you think I'd be a good fit for your team.

Contact: liminy2@illinois.edu
Office: Room 4111, Thomas M. Siebel Center, Urbana, IL 61801.

News
10/11/2022 Submitted another paper to USENIX Security 2023! Big thanks to everyone!
08/19/2022 Submitted a paper to IEEE S&P (Oakland) 2023! Thanks a lot to my advisor and collaborators!
05/23/2022 First day at IBM Research (New York) as a visiting scholar.
I work with Muhammed Fatih Bulut and Constantin Adam on network intrusion detection.
05/17/2021 First day at TikTok (ByteDance) as a Security Engineering Intern (focus: spam detection).
Thanks for the opportunity, Dr. Yu Ding and Dr. Hui Cao!
04/09/2021 Just passed my qualifier exam. Now I'm officially a Ph.D. candidate!
02/24/2021 Our paper got accepted to the DLS workshop. We release a new PE malware dataset for ML research [download link].
11/30/2020 I will be serving as a Shadow PC at Oakland 2021.
09/30/2020 Our USENIX Security'21 paper got accepted! Thanks for everyone who helped me!
Publications
Conference Papers
[USENIX Security'21] CADE: Detecting and Explaining Concept Drift Samples for Security Applications
Limin Yang, Wenbo Guo, Qingying Hao, Arridhana Ciptadi, Ali Ahmadzadeh, Xinyu Xing, Gang Wang
PDF / Supplementary PDF / Code / Slides / Video / Artifact Evaluated
TL;DR: Contrastive learning can help detect drifting samples from previously unseen classes and distance-based explanation can find out why such drifting samples are different from existing classes.

[USENIX Security'20] Measuring and Modeling the Label Dynamics of Online Anti-Malware Engines
Shuofei Zhu, Jianjun Shi, Limin Yang, Boqin Qin, Ziyi Zhang, Linhai Song, Gang Wang
PDF / Data / Artifact Evaluated
TL;DR: How to aggregate VirusTotal labels more properly?
[IMC'19] Opening the Blackbox of VirusTotal: Analyzing Online Phishing Scan Engines
Peng Peng, Limin Yang, Linhai Song, Gang Wang
PDF / Data
TL;DR: Control simple phishing sites to see how bad and inconsistent of the URL detection provided by VirusTotal and security vendors' own APIs.
[USENIX Security'18] Understanding the Reproducibility of Crowd-reported Security Vulnerabilities
Dongliang Mu, Alejandro Cuevas, Limin Yang, Hang Hu, Xinyu Xing, Bing Mao, Gang Wang
PDF / Data
TL;DR: Provide quantitive evidence on the prevalence of missing information in vulnerability reports and low reproducibility by manually reproduce 368 memory corruption bugs.
[GLOBECOM'17] VulDigger: A Just-in-Time and Cost-Aware Tool for Digging Vulnerability-Contributing Changes
Limin Yang, et al.
PDF
TL;DR: Use metadata and heuristics to predict whether a git commit introduced a vulnerability.
Journal / Workshop Papers
[DLS'21] BODMAS: An Open Dataset for Learning based Temporal Analysis of PE Malware
Limin Yang, Arridhana Ciptadi, Ihar Laziuk, Ali Ahmadzadeh, Gang Wang
PDF / Slides / Data / Code
TL;DR: We collaborate with Blue Hexagon to release an open Windows PE malware dataset with timestamped metadata as well as curated malware family labels.
[SafeThings'20] A Case Study of the Security Vetting Process of Smart-home Assistant Applications
Hang Hu, Limin Yang, Shihan Lin, Gang Wang
PDF
TL;DR: Verify that replay attack and SQL injection are feasible in Amazon Alexa / Google Home apps.
[PPNA'17] Characterizing User Behaviors in Location-based Find-and-Flirt Services: Anonymity and Demographics
Minhui Xue, Limin Yang, Keith W. Ross, Haifeng Qian
PDF
TL;DR: Who used the WeChat "People Nearby" feature more often?
Internships
IBM Research Visiting Scholar (Research Intern) , New York, US, 05/2022 – 08/2022
Mentors: Dr. Muhammed Fatih Bulut and Dr. Constantin Adam
TikTok Security Engineering Intern, California, US, 05/2021 – 08/2021
Mentors: Dr. Dazhuo Li, Dr. Hamed Ashouri, and Dr. Hui Cao
Penn State Research Intern, Pennsylvania, US, 09/2017 – 02/2018
Mentors: Dr. Xinyu Xing and Dr. Gang Wang
Peking University Exploit Intern, Beijing, China, 07/2015 – 08/2015
Mentors: Dr. Yu Ding and Dr. Xinhui Han.
Awards
2021 CCS Student Conference Grant
2017 ECNU Graduate Student Overseas Research Scholarship
2013-2015 ECNU Top-notch Innovative Personnel Training Plan
Teaching
2019 Spring CS-4264 Principles of Computer Security, Virginia Tech, Teaching Assistant
2018 Fall CS-3114 Data Structures and Algorithms, Virginia Tech, Teaching Assistant
Professional Services
[Oakland'21] IEEE Symposium on Security and Privacy, Student PC
[Patterns'21] Patterns (a data science journal by Cell Press), Reviewer
Upcoming Deadlines
Oakland'23 April 1, August 19, December 2, 2022. San Francisco, CA.
USENIX Sec'23 June 7, October 11, 2022; February 7, 2023. Anaheim, CA.
CCS'22 January 14, May 2, 2022. Los Angeles, CA.
NDSS'23 May 13, July 29, 2022. San Diego, CA.

Miscellaneous I'm also a minimalism photographer: whyisyoung.com

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