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Projects

Security Analysis of Unmanned Aerial Vehicles

Mar 2015 ─ Sep 2015

We studied the risks of UAVs and conducted an empirical analysis of three popular DJI UAVs. We discovered a series of vulnerabilities, including insecure communication channels, misuse of cryptography, and insecure UAV activation and developer authorization.

Source Code Author Deanonymization

Nov 2015 ─ Jan 2016

In this work, we explored neural network based approaches (Recurrent neural network) towards the source code author deanonymization problem. With a dataset extracted from Google Code Jam, our char-level model performs competitively on normal size dataset comparing to previous state-of-art work.

Angora: Efficient, Coverage-Directed Fuzzing

Oct 2016 ─ May 2017

We propose Angora, a new mutation-based fuzzer that outperforms the state-of-the-art fuzzers by a wide margin. We define a measurable objective, branch coverage, and design several key techniques towards this objective, such as scalable, efficient byte-level taint tracking, context-sensitive branch count, and selection of conditional statements that are easier to fuzz.

afl_pin_mode

Sep 2017

Yet another AFL instrumentation tool implemented by Intel Pin. [code]


Publications