Inline Detection of DGA Domains Using Side Information

no code implementations • 12 Mar 2020 • Raaghavi Sivaguru, Jonathan Peck, Femi Olumofin, Anderson Nascimento, Martine De Cock

We found that the DGA classifiers that rely on both the domain name and side information have high performance and are more robust against adversaries.

Adversarial Attack

CharBot: A Simple and Effective Method for Evading DGA Classifiers

no code implementations • 3 May 2019 • Jonathan Peck, Claire Nie, Raaghavi Sivaguru, Charles Grumer, Femi Olumofin, Bin Yu, Anderson Nascimento, Martine De Cock

In this work, we present a novel DGA called CharBot which is capable of producing large numbers of unregistered domain names that are not detected by state-of-the-art classifiers for real-time detection of DGAs, including the recently published methods FANCI (a random forest based on human-engineered features) and LSTM. MI (a deep learning approach).

Adversarial Attack