Towards Optimal Use of Exception Handling Information for Function Detection
Chengbin Pang; Ruotong Yu; Dongpeng Xu; Eric Koskinen; Georgios Portokalidis; Jun Xu · 2021 · arXiv
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Function entry detection is critical for security of binary code. Conventional methods heavily rely on patterns, inevitably missing true functions and introducing errors. Recently, call frames have been used in exception-handling for function start detection. However, existing methods have two problems. First, they combine call frames with heuristic-based approaches, which often brings error and uncertain benefits. Second, they trust the fidelity of call frames, without handling the errors that are introduced by call frames. In this paper, we first study the coverage and accuracy of existing a
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Metadata source: arXiv