Matthew Gaber: Peekaboo Transformer Models

Finding automated AI techniques to proactively defend against malware has become increas-
ingly critical. The ability of an AI model to correctly classify novel malware is dependent
on the quality of the features it is trained with. In turn, the authenticity and quality of the features
is dependent on the analysis tool and the dataset. Peekaboo, a Dynamic Binary Instrumen-
tation tool defeats evasive malware to capture its genuine behavior. Transformer models
trained with Peekaboo data excel in detecting new malicious functions, outperforming
prior approaches in novel ransomware detection.

寻找自动化AI技术以主动防御恶意软件已变得日益关键。AI模型正确分类新型恶意软件的能力取决于其训练所用特征的质量，而特征的真实性与质量又依赖于分析工具和数据集。Peekaboo是一款动态二进制插桩工具（Dynamic Binary Instrumentation tool），可破解规避型恶意软件并捕获其真实行为。使用Peekaboo数据训练的Transformer模型在检测新型恶意函数方面表现卓越，在新型勒索软件检测任务中性能优于现有方法。