Enhancing IoT Network Security through AIDriven Intrusion Detection with Hybrid AutoencoderGAN Fusion
RA Mahajan, SS Dari, R Dhabliya, G Michael… - Proceedings of the 5th …, 2023 - dl.acm.org
The rapid growth of Internet of Things (IoT) IoT devices has changed how we connect and
interact with our environment. This advancement has also complicated network security. As …
interact with our environment. This advancement has also complicated network security. As …
Evaluation of Deep CNN-BiLSTM Model on Diverse Datasets
L Nguyet, TH Hai - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
In the field of network intrusion detection, a wide range of machine learning and deep
learning models have been developed, including the successful CNN-BiLSTM [1] model …
learning models have been developed, including the successful CNN-BiLSTM [1] model …
[PDF][PDF] KRİTİK ALTYAPILARA YÖNELİK DERİN ÖĞRENME TABANLI SALDIRI TESPİT SİSTEMİ TASARIMI
HCAN ALTUNAY - 2023 - acikerisim.karabuk.edu.tr
Enerji, ulaşım, üretim tesisleri gibi kritik altyapıya sahip sistemlerin siber saldırılara karşı
korunması ulusal güvenlik için kritik öneme sahiptir. Gelişen teknoloji ile birlikte kritik …
korunması ulusal güvenlik için kritik öneme sahiptir. Gelişen teknoloji ile birlikte kritik …
Cybersecurity Using Hybrid Type Model for Classification Through SCO Optimization Technique
The effectiveness of Network Intrusion Detection Systems (NIDS) in recognizing complex
attacks is hindered by evasion strategies like polymorphic malware and encrypted traffic …
attacks is hindered by evasion strategies like polymorphic malware and encrypted traffic …
Network Intrusion Detection with Feature Elimination and Selection Using Deep Learning
In the contemporary digital landscape, marked by an ever-increasing number of individuals
seeking to exploit vulnerabilities in systems and cause immense damage to users, it …
seeking to exploit vulnerabilities in systems and cause immense damage to users, it …
[PDF][PDF] Intrusion Detection with Deep Learning Classifiers: A Synergistic Approach of Probabilistic Clustering and Human Expertise to Reduce False Alarms
Intrusion detection systems (IDS) have seen an increasing number of proposals by
researchers utilizing deep learning (DL) to safeguard critical networks. However, they often …
researchers utilizing deep learning (DL) to safeguard critical networks. However, they often …
Enhancing Intrusion Detection System (IDS) Through Deep Packet Inspection (DPI) with Machine Learning approaches
KA Bathiri, M Vijayakumar - 2024 International Conference on …, 2024 - ieeexplore.ieee.org
In today's era of ever connecting devices and exponential growth in the number of small
networks in every digital workspace, security concerns are also growing rapidly. Intrusion …
networks in every digital workspace, security concerns are also growing rapidly. Intrusion …
Conditional Generative Adversarial Network with Optimal Machine Learning Based Intrusion Detection System
K Hemavathi, R Latha - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Intrusion Detection System (IDS) is intended to analyse and monitoring system actions or
network traffic to recognize and relate to capable security attacks or intrusions. If managing …
network traffic to recognize and relate to capable security attacks or intrusions. If managing …
Light-Weight Slow-Rate Attack Detection Framework for Resource-Constrained Industrial Cyber-Physical Systems
Abstract Industrial Cyber-Physical Systems (ICPS) are heterogenous computer systems
interacting withphysical processes in an industrial environment. The high degree of …
interacting withphysical processes in an industrial environment. The high degree of …
ME-IDS: An Ensemble Transfer Learning Framework Based on Misclassified Samples for Intrusion Detection Systems
A Ghosh - 2023 - dalspace.library.dal.ca
In our digitally interconnected world, the demand for robust security measures has become
increasingly apparent, given the escalating threat of cyberattacks on the Internet. Intrusion …
increasingly apparent, given the escalating threat of cyberattacks on the Internet. Intrusion …