… In order to further enhance the performance of machine learning based IDS, we propose the
Big Data based Hierarchical Deep Learning System (BDHDLS… Each deep learning model in …

… techniques that can handle these types of data that have big data nature in detecting … a
big data-aware deep learning method to design an efficient and effective Intrusion Detection …

… network intrusions, using a stacked auto-encoder with a soft-max classifier. With work still …
of intrusion detection in a big data environment, we propose a hybrid deep learning model …

… As we discussed some of the machine learning and data mining techniques for intrusion
detection on big data analytics, we study some of the recent works on deep learning works …

… detect intrusions on a network with multiple data classification tasks in this research work.
The proposed MR-IMID processes big data sets reliably using … -time for intrusion detection. In …

… performing the intrusion in near real-time in big data environments, we propose a Long-Lasting
Intrusion Detection Model. The proposed model is implemented in a twofold manner. …

… has been obsolete in the age of big data. To solve the problems of low accuracy and feature
engineering in intrusion detection, a traffic anomaly detection model BAT is proposed. The …

… Signature-based Intrusion detection systems are not suitable anymore to be … , we propose
using deep learning with big data to solve this problem. Big data allows us to use big datasets …

… in training large data sets. However, several applications are utilizing machine learning (ML)
methods … This section focuses on the most commonly used datasets for intrusion detection. …

… machine learning method by combining the feature selection method, representing the
supervised learning and data … This research proposes a hybrid machine learning method by …