Valkyrie: Behavioral malware detection using global kernel-level telemetry data
作者： Sven Krasser , Brett Meyer , Patrick Crenshaw
DOI: 10.1109/MLSP.2015.7324334
关键词:
摘要: The growth in malware remains a major challenge to Internet security. In this paper, we present Valkyrie, classification system that is able identify malicious binaries purely based on behavioral traits gathered from large-scale telemetry submitted by endhosts using lightweight sensor component. Valkyrie utilizes the Apache Spark data processing framework and therefore process large volume of real-world short amount time. addition, since conducts all its heavy computation cloud, it imposes minimal load endpoints. achieves high confidence predictions at very low false positive rate, making suitable solution for use with production systems.
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