project

Defeating Evasive Malware with Peekaboo: Extracting Authentic Malware Behavior with Dynamic Binary Instrumentation


Provided by   Edith Cowan University

Research Project

Researchers: Edith Cowan University (Managed by) ,  Helge Janicke (Associated with) ,  Matthew Gaber (Associated with) ,  Mohiuddin Ahmed (Associated with)

Full description

The accuracy and effectiveness of AI for malware detection is dependent on the quality and quantity of the features it is trained with. That is, an analysis tool that forces malware to expose it malicious intent and then extracts genuine features, along with large and diverse repositories of malware and benign software, are necessary to train accurate AI models. This research had two primary objectives: investigation of the evasive techniques used by modern malware and the creation of the Peekaboo DBI tool to extract authentic behavior from live malware samples.

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Contact Information

Matthew Gaber