Feb. 14, 2024, 5:10 a.m. | Noble Saji Mathews Yelizaveta Brus Yousra Aafer Meiyappan Nagappan Shane McIntosh

cs.CR updates on arXiv.org arxiv.org

Despite the continued research and progress in building secure systems, Android applications continue to be ridden with vulnerabilities, necessitating effective detection methods. Current strategies involving static and dynamic analysis tools come with limitations like overwhelming number of false positives and limited scope of analysis which make either difficult to adopt. Over the past years, machine learning based approaches have been extensively explored for vulnerability detection, but its real-world applicability is constrained by data requirements and feature engineering challenges. Large Language …

analysis android applications building continue cs.ai cs.cr cs.se current detection dynamic dynamic analysis false positives language language models large limitations progress research scope static and dynamic analysis strategies systems tools vulnerabilities vulnerability vulnerability detection

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