Traffic Analysis-Based Cybersecurity Intrusion Detection Through Automated Guided Attention Federated Graph Neural Network
S Ghosh - Applied Soft Computing, 2024 - Elsevier
The increasing demand for the Internet of Things (IoT) and various distributed devices has
highlighted the need for reliable and effective intrusion detection systems to safeguard …
highlighted the need for reliable and effective intrusion detection systems to safeguard …
A Machine Learning-Based Framework with Enhanced Feature Selection and Resampling for Improved Intrusion Detection
Intrusion Detection Systems (IDSs) play a crucial role in safeguarding network
infrastructures from cyber threats and ensuring the integrity of highly sensitive data …
infrastructures from cyber threats and ensuring the integrity of highly sensitive data …
Auto evaluation for Essay Assessment Using a 1D Convolutional Neural Network
NG Pasaribu, G Budiman, ID Irawati - IEEE Access, 2024 - ieeexplore.ieee.org
Traditional assessment methods often face a trade-off between accessibility and in-depth
evaluation. While multiple-choice exams offer easy grading, they may limit the ability to …
evaluation. While multiple-choice exams offer easy grading, they may limit the ability to …
Survey of Intrusion Detection Techniques in Cloud Computing
SM Othman, AY Al-mutawkkil… - Sana'a University Journal …, 2024 - journals.su.edu.ye
With the continued development of cloud computing environments, security measures have
become more im-portant than ever. Intrusion detection systems (IDS) are considered one of …
become more im-portant than ever. Intrusion detection systems (IDS) are considered one of …
[PDF][PDF] Network intrusion detection system based on information gain with deep bidirectional long short-term memory
WT Valavan, N Joseph, GU Srikanth - International Journal of Intelligent …, 2024 - inass.org
Network Intrusion Detection System (NIDS) plays a major role in maintaining the integrity
and security in computer networks. These systems are created to detect and acknowledge …
and security in computer networks. These systems are created to detect and acknowledge …
CHOS_LSTM: Chebyshev Osprey optimization-based model for detecting attacks
This paper explores the application of Chebyshev Osprey optimization-based Long Short
Term Memory (ChOs_LSTM) for intrusion detection, utilizing input from the CICIDS-2018 …
Term Memory (ChOs_LSTM) for intrusion detection, utilizing input from the CICIDS-2018 …
Prediction of Cyber Attacks Utilizing Deep Learning Model using Network/Web Traffic Data
B Kannan, M Sakthivanitha… - 2024 3rd International …, 2024 - ieeexplore.ieee.org
Nowadays, cyber-attacks are growing predominantly due to the development of
technologies. It will lead to financial losses to a company and the other problems related to …
technologies. It will lead to financial losses to a company and the other problems related to …
Feature Selection using Improved Nomadic People Optimizer in Intrusion Detection
Intrusion Detection (ID) in network communication and Wireless Sensor Networks (WSN) is
a big challenge that has grown with the rapid development of these technologies. Various …
a big challenge that has grown with the rapid development of these technologies. Various …
[PDF][PDF] An Accurate Approach for Intrusion Detection System Using Chaotic Maps, NPO, and SVM.
The internet and technological advancements have facilitated faster communication and
information sharing. However, cybercrime, including malware, phishing, and ransomware …
information sharing. However, cybercrime, including malware, phishing, and ransomware …
An innovative model for an enhanced dual intrusion detection system using LZ‐JC‐DBSCAN, EPRC‐RPOA and EG‐GELU‐GRU
The rise of suspicious activities in network communication, driven by increased internet
accessibility, necessitates the development of advanced intrusion detection systems (IDS) …
accessibility, necessitates the development of advanced intrusion detection systems (IDS) …