DA-GAN: Domain Adaptation for Generative Adversarial Networks-assisted Cyber Threat Detection

RESEARCH CREW

6:31 24/11/2022

The rising development of machine learning (ML) techniques has become the motivation for research in applying their outstanding features to facilitate intelligent intrusion detection systems (IDSs). However, ML-based solutions also have drawbacks of high false positive rates and vulnerability to sophisticated attacks such as adversarial ones. Therefore, continuous evaluation and improving those systems are necessary tasks, which can achieve by simulating mutated real-world attack scenarios. Taking advantage of the Generative Adversarial Network (GAN) and Domain Adaptation technique, our approach proposes DA-GAN, a framework that can generate mutated network attack flows. Those crafted flows then work as supplemental training data for ML-based IDS to improve its robustness in dealing with new and complicated attacks. Our framework is implemented and evaluated via experiments on the public CIC-IDS2017 and CIC-IDS2018 datasets. The results prove the effectiveness of the proposed framework in continuously strengthening ML-based IDS in the fight against network attack actors.

TIN LIÊN QUAN

An Approach of Adaptive Cyber Deception for Active Cyber-attack Defense Method based on Deep Reinforcement Learning

The diverse landscape of network models, including Software-Defined Networking (SDN), Cloud Computing (C2), and Internet of Things (IoT), is evolving to meet the demands of flexibility and performance. However, these environments face numerous security challenges due to cyber-attack complexity. Traditional defense mechanisms are no longer effective against modern attacks. Therefore,...

Multimodal Deep Learning Feedback for Generating Evasive Malware Samples against Malware Detector

As data driven-based Windows malware detectors become increasingly prevalent, the need for robust evaluation and enhancement of adversarial malware generation techniques also becomes imperative, as malicious actors will adapt and enhance their malware to evade detection. There are numerous works that introduce new techniques or enhancements for adversarial malware. One...

Medichain: A multi-chain based system for managing prescription medications using Zero Knowledge Proofs

The abuse of prescription medications has become a severe public health crisis fueled by limited coordination and oversight across healthcare systems. Current frameworks lack interoperability between doctors, pharmacies, and regulators, enabling abusive practices like doctor shopping and pharmacy hopping. To address these issues, this research proposes Medichain, a novel multichain-based...