Eran had contributed to a new paper by the LAMBDA Lab headed by Prof. Irad Ben-Gal. The paper, by Doron Cohen, Or Naim, Eran Toch, and Irad Ben-Gal, suggests a new way to categorize crack websites, which contain a mixture of harmless and malware software.

You can download the paper from here.

The basic observation is that crack websites need to balance two opposing requirements to successfully function: Escaping malware detection tools while signaling to users that they have free software for download. Therefore,  we hypothesize that in many cases, they preserve specific visual designs that signal the website’s function to potential users (such as particular colors, text fonts, shapes, and sizes.)

The study shows that machine learning models for categorizing Crack and Malicious websites can considerably benefit from using design features.

We report on two experiments based on unbalanced datasets and show that classification by using design features can reach a categorization accuracy of over 90% with an F1-score over 77% in some instances.