Deep neural network based real-time intrusion detection system
SP Thirimanne, L Jayawardana, L Yasakethu… - SN Computer …, 2022 - Springer
In recent years, due to the rapid growth in network technology, numerous types of intrusions
have been uncovered that differ from the existing ones, and the conventional firewalls with …
have been uncovered that differ from the existing ones, and the conventional firewalls with …
Artificial Neural Network Technique for DDOS Attack Prediction in Cyber-IOT System
M Asad, RK Tiwari - 2023 3rd International Conference on …, 2023 - ieeexplore.ieee.org
An intrusion-detection IoT framework is designed to analyze unauthorized access or security
breaches in IoT networks. These systems typically use a combination of hardware and …
breaches in IoT networks. These systems typically use a combination of hardware and …
Performance Evaluation of Network Intrusion Detection Using Machine Learning
S Gnanasivam, D Tveter, N Dinh - 2024 IEEE International …, 2024 - ieeexplore.ieee.org
The development of 5G network and beyond has led to an explosion of data generation. It is
therefore crucial to have an intrusion detection system (IDS) to detect and remove malicious …
therefore crucial to have an intrusion detection system (IDS) to detect and remove malicious …
Deep learning for intelligent transportation: A method to detect traffic violation
M Rajagopal, R Sivasakthivel - AIP Conference Proceedings, 2023 - pubs.aip.org
Smart transportation is being envisaged as an important parameter in building smart cities.
Although conceptualized to have major advantages, lack of intelligent systems makes more …
Although conceptualized to have major advantages, lack of intelligent systems makes more …
A Comprehensive Analysis of Machine Learning Models for IDS
P Shah, P Shah, N Jadav - International Conference on Smart Computing …, 2024 - Springer
Intrusion detection systems (IDS) play a vital role in protecting computer networks from
malicious activities. The effectiveness of IDS heavily relies on the quality and suitability of …
malicious activities. The effectiveness of IDS heavily relies on the quality and suitability of …
GuardianAI: Smart Intrusion Detection for Modern Threats
M SAIRAJKUMAR - 2024 - researchsquare.com
Finding and stopping breaches is now essential in the rapidly evolving world of
cybersecurity. This work involves a range of machine learning algorithms for intrusion …
cybersecurity. This work involves a range of machine learning algorithms for intrusion …
[PDF][PDF] A DEEP ATTENTION FRAMEWORK FOR NETWORK ANOMALY DETECTION
V EL, OR NET - 2023 - docs.neu.edu.tr
This dissertation introduces an innovative transformer architecture specifically designed for
deep learning-based multi-class classification tasks. The motivation behind this research …
deep learning-based multi-class classification tasks. The motivation behind this research …
A Comprehensive Analysis of Machine Learning Models for IDS Check for updates
P Shah, P Shah, N Jadav - … : Proceedings of SmartCom 2024, Volume 3 - books.google.com
Intrusion detection systems (IDS) play a vital role in protecting computer networks from
malicious activities. The effectiveness of IDS heavily relies on the quality and suitability of …
malicious activities. The effectiveness of IDS heavily relies on the quality and suitability of …
An Incident Management System Design to Protect Critical Infrastructures from Cyber Attacks
U Gürtürk, ZG Aydın - Journal of Mathematical Sciences and Modelling - dergipark.org.tr
In recent years, there has been a noticeable trend toward targeted threats to information
security, where companies are now leveraging vulnerabilities and risks associated with …
security, where companies are now leveraging vulnerabilities and risks associated with …