Year: 2024
Type: conference-paper
Abstract: Software protection researchers often struggle with the evaluation of MATE software protections and attacks.Evaluations often are incomplete and not representative of the practice.This can in part be explained by a lack of standardized, generally applicable models, tools, and methodologies for evaluating how reverse engineering attack strategies are executed.The framework of related components proposed in this paper is an attempt to provide exactly that.It includes a meta-model and supporting tools for modeling the knowledge that reverse engineers acquire as they execute their strategies, a meta-model to estimate the required effort of those strategies, and tools to capture strategic activities from data streams collected during human reverse engineering experiments.Their use is demonstrated on three example reverse engineering strategies.
Institutions: Ghent University, University of Arizona
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4404515083