DReLAB - Deep REinforcement Learning Adversarial Botnet: A benchmark dataset for adversarial attacks against botnet Intrusion Detection Systems

DReLAB - Deep REinforcement Learning Adversarial Botnet: A benchmark dataset for adversarial attacks against botnet Intrusion Detection Systems

We present the first dataset that aims to serve as a benchmark to validate the resilience of botnet detectors against adversarial attacks. This dataset includes realistic adversarial samples that are generated by leveraging two widely used Deep Reinforcement Learning (DRL) techniques. These adversar...

Full description

Bibliographic Details
Main Authors: Andrea Venturi, Giovanni Apruzzese, Mauro Andreolini, Michele Colajanni, Mirco Marchetti
Format: Article
Language:English
Published: Elsevier 2021-02-01
Series:Data in Brief
Subjects:
Cyber security
Adversarial attacks
Deep reinforcement learning
Intrusion detection system
Botnet
Online Access:http://www.sciencedirect.com/science/article/pii/S2352340920315110

Similar Items

Similar Items