Attacklets: Modeling High Dimensionality in Real World Cyberattacks

Cuneyt Gurcan Akcora, Jonathan Z. Bakdash, Yulia R. Gel, Murat Kantarcioglu, Laura R. Marusich, Bhavani M. Thuraisingham

Abstract: We introduce attacklets, a novel approach to model the high dimensional interactions in cyberattacks. Attacklets are implemented using a real-world dataset of cyberattacks from the Verizon Data Breach Investigation Report. Whereas the commonly used attack graphs model the action sequences of attackers for specific exploits, attacklets model general attributes and states of each attack separately. Attacklets may inform the number and types of attributes across a wide range of cyberattacks. These structural properties can then be used in machine learning models to classify and predict future cyberattacks.