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Computer Science, Computer Security, Data Privacy, Blockchain

Los Angeles, CA
March 26, 2018

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Jun Tang

323-***-**** **** Oak St. Los Angeles, CA-90007 EDUCATION

Ph.D. Student, Computer Science, University of Southern California Sep 2016 - Present Courses: Blockchain Technology and Applications, Big Data (Differential) Privacy, Advanced Computer Security, Advanced Analysis of Algorithms, Structure & Dynamics of Networked Information Master of Science in Computer Science, University of Southern California Exp. May 2018 Bachelor of Science in Computer Science, Harbin Institute of Technology, China July 2014 Specialization: Information Security


Programming Languages: Python, C, C++, x86/x64/ARM Assembly, Scheme, SML, Haskell, Rust, Bash Reverse Engineering: IDA Pro, Hopper Tools: Bitcoin, Blockchain, scikit-learn, Django, Git, Latex, Numpy, Linux, IoT Database: SQL Server, SQLite PROFESSIONAL EXPERIENCE & PROJECTS

Research Assistant, University of Southern California, Privacy Research Group Sep 2016 - Dec 2017 Privacy Loss in Apple’s Implementation of Differential Privacy

• Reverse engineered and figured out Apple’s Differential Privacy System via static & dynamic analysis

• Proved its privacy loss exceeds the levels typically considered acceptable by the differential privacy research community

• Very likely pushed Apple to publish the white paper of its implementation

• Highly possible influenced Apple to change its Differential Privacy parameters on iOS & macOS to achieve better privacy

• Got press report from Wired; work mentioned by EFF and many famous security researchers: e.g., Matthew Green Privacy in Smart Home Devices

• Analyzed the network traffic, Skills (apps for Amazon Echo), and privacy policies for Skills

• Found out that most Skills lack updated or new privacy policies specifically for smart home devices

• Demonstrated potential privacy risks due to lacking modern location and list access permission model

• Short paper accepted by HotPETS 2017

Full-time Intern, Microsoft Research Asia, System and Algorithm Group, Award of Excellence July 2015 - May 2016 Efficient Learning on IoT Devices - To generating rules to control IoT devices automatically and efficiently

• Proposed an efficient stream processing learning algorithm: a decision tree algorithm that can evolve based on new data

• Built a system that generates IFTTT rules based on learning results Full-time Intern, Microsoft Research Asia, Mobile and Sensing Systems Group, Award of Excellence July 2013 - June 2014 Contextual Fuzzing for Mobile App Testing -To uncover more app crashes and performance outliers in a much shorter time

• Studied the correlation between app (on the Windows Store) crashes and app’s resource consumptions

• Designed a learning algorithm that identifies conditions in which previously unseen apps will crash

• In charge of the back-end for a cloud-based web service which can automatically test mobile apps and generate the analysis report; This service was used to test most popular Windows apps, such as Weather, News

• Paper accepted by MobiCom

Human-Building Analytics - To dispatch elevators efficiently by leveraging human behavioral patterns

• Created a new elevator dispatch algorithm which leverages real-world human behavioral usage patterns

• Evaluated the algorithm with simulations: compared with state of the art, it responded 80% faster and saved 8.6% travel distance

• Poster accepted by BuildSys

Intern, Harbin Institute of Technology, Machine Intelligence and Translation Lab Oct 2012 - June 2013 Meta-Translation System - To generate a better translation based on existing translation solutions

• Designed a Natural Language Processing algorithm to automatically generate better translation based on existing translations

• Built a web service with Django framework based on the algorithm and the web service was used by the lab members daily PUBLICATIONS

Privacy Loss in Apple’s Implementation of Differential Privacy, arXiv, 2017. Popular Press: Wired, EFF Privacy in the Amazon Alexa Skills Ecosystem, HotPETs, 2017 Caiipa: Automated Large-scale Mobile App Testing through Contextual Fuzzing, MobiCom, 2014 On Human Behavioral Patterns in Elevator Usages, BuildSys, 2013

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