Can I read Is Function Similarity Over-Engineered? Building a Benchmark on EtoBox?

Is Function Similarity Over-Engineered? Building a Benchmark by Saul, Rebecca; Liu, Chang; Fleischmann, Noah; Zak, Richard; Micinski, Kristopher; Raff, Edward; Holt, James is a scholarly article available to read on EtoBox.

What is Is Function Similarity Over-Engineered? Building a Benchmark about?

Binary analysis is a core component of many critical security tasks, including reverse engineering, malware analysis, and vulnerability detection. Manual analysis is often time-consuming, but identifying commonly-used or previously-seen functions can reduce the time it takes to understand a new file. However, given the complexity of assembly, and the NP-hard nature of determining function equivalence, this task is extremely difficult. Common approaches often use sophisticated disassembly and decompilation tools, graph analysis, and other expensive pre-processing steps to perform function similarity searches over some corpus. In this work, we identify a number of discrepancies between the current research environment and the underlying application need. To remedy this, we build a new benchmark, REFuSE-Bench, for binary function similarity detection consisting of high-quality datasets and tests that better reflect real-world use cases. In doing so, we address issues like data duplication and accurate labeling, experiment with real malware, and perform the first serious evaluation of ML binary function similarity models on Windows data. Our benchmark reveals that a new, simple basline

Author

Saul, Rebecca; Liu, Chang; Fleischmann, Noah; Zak, Richard; Micinski, Kristopher; Raff, Edward; Holt, James

Published

2024

Language

EN