DeepAI AI Chat
Log In Sign Up

A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection

by   Rahul Kale, et al.
Singapore Technologies Engineering Ltd

Cyber intrusion attacks that compromise the users' critical and sensitive data are escalating in volume and intensity, especially with the growing connections between our daily life and the Internet. The large volume and high complexity of such intrusion attacks have impeded the effectiveness of most traditional defence techniques. While at the same time, the remarkable performance of the machine learning methods, especially deep learning, in computer vision, had garnered research interests from the cyber security community to further enhance and automate intrusion detections. However, the expensive data labeling and limitation of anomalous data make it challenging to train an intrusion detector in a fully supervised manner. Therefore, intrusion detection based on unsupervised anomaly detection is an important feature too. In this paper, we propose a three-stage deep learning anomaly detection based network intrusion attack detection framework. The framework comprises an integration of unsupervised (K-means clustering), semi-supervised (GANomaly) and supervised learning (CNN) algorithms. We then evaluated and showed the performance of our implemented framework on three benchmark datasets: NSL-KDD, CIC-IDS2018, and TON_IoT.


page 1

page 6


A Case Study on Using Deep Learning for Network Intrusion Detection

Deep Learning has been very successful in many application domains. Howe...

Active Learning for Network Intrusion Detection

Network operators are generally aware of common attack vectors that they...

Near Real-time Learning and Extraction of Attack Models from Intrusion Alerts

Critical and sophisticated cyberattacks often take multitudes of reconna...

Leveraging Siamese Networks for One-Shot Intrusion Detection Model

The use of supervised Machine Learning (ML) to enhance Intrusion Detecti...

Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection

Deep learning has recently demonstrated state-of-the art performance on ...

Anomaly-Based Intrusion Detection by Machine Learning: A Case Study on Probing Attacks to an Institutional Network

Cyber attacks constitute a significant threat to organizations with impl...