More about HKUST
Towards Industrial-Scale Software Binary Analysis
PhD Thesis Proposal Defence
Title: "Towards Industrial-Scale Software Binary Analysis"
by
Mr. Anshunkang ZHOU
Abstract:
Software binaries form the operational backbone of modern industrial
systems, from critical infrastructure and medical devices to autonomous
vehicles and IoT ecosystems. However, vulnerabilities in these binaries,
such as memory corruption and logic errors, pose significant risks,
including catastrophic safety failures and financial losses. Traditional
methods for ensuring the safety of industrial software require access to
source code and interference with the building process to obtain analyzable
artifacts (e.g., intermediate representations). Those approaches are
impractical and imprecise in industrial-scale environments due to the
complexity of modern building systems and the widespread usage of
third-party libraries.
This proposal introduces two key techniques for industrial-scale software
binary analysis to overcome the above limitations. First, we propose a new
binary lifter Plankton together with two new algorithms that can fill the
gaps between the low- and high-level code to produce high-quality LLVM
intermediate representations (IRs) from binaries with debug information,
enabling non-intrusive full-fledged static analysis with minor precision
loss. Second, we propose Arcturus, a new binary similarity analysis
technique that can achieve high code coverage and high accuracy
simultaneously by manipulating program execution under the guidance of code
reachability. Our method has already demonstrated real-world impact by
deploying to industrial environments and identifying critical
vulnerabilities in widely used systems.
Date: Tuesday, 27 May 2025
Time: 10:00am - 12:00noon
Venue: Room 2128A
Lift 19
Committee Members: Prof. Charles Zhang (Supervisor)
Dr. Shuai Wang (Chairperson)
Dr. Dongdong She