A Deep Learning Approach to Network Intrusion Detection Using Deep Autoencoder.
S Moraboena, G Ketepalli… - Revue d'Intelligence …, 2020 - search.ebscohost.com
The security of computer networks is critical for network intrusion detection systems (NIDS).
However, concerns exist about the suitability and sustainable development of current …
However, concerns exist about the suitability and sustainable development of current …
Anomaly Detection in Credit Card Transaction using Deep Learning Techniques
G Ketepalli, S Tata, S Vaheed… - 2022 7th International …, 2022 - ieeexplore.ieee.org
One of the most convenient ways to pay is by using a credit card. For both online and offline
transactions, it is a handy tool. Credit card numbers are used extensively in online …
transactions, it is a handy tool. Credit card numbers are used extensively in online …
Feature Extraction using LSTM Autoencoder in Network Intrusion Detection System
G Ketepalli, P Bulla - 2022 7th International Conference on …, 2022 - ieeexplore.ieee.org
IDS (intrusion detection systems) use analysis of network traffic patterns to detect incidents
of hacking. It is essential to do feature extraction in order to minimize the computational cost …
of hacking. It is essential to do feature extraction in order to minimize the computational cost …
An effective ensemble classification framework for intrusion detection system using LSTM autoencoder
G Ketepalli, P Bulla - Journal of Intelligent & Fuzzy Systems, 2024 - content.iospress.com
In intrusion detection, the curse of dimensionality and the trade-off between maintaining a
low false alarm rate and achieving a high detection rate are significant challenges. This …
low false alarm rate and achieving a high detection rate are significant challenges. This …