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Incremental Adversarial Learning for Polymorphic Attack Detection
AI-based Network Intrusion Detection Systems (NIDS) provide effective mechanisms for
cybersecurity analysts to gain insights and thwart several network attacks. Although current …
cybersecurity analysts to gain insights and thwart several network attacks. Although current …
Comparison of convolutional neural networks, long short-term memory networks, and recurrent neural networks for intrusion detection system
In recent years, the rapid growth of internet usage has led to an increase in cyber threats
and attacks. To combat these threats, the development of effective intrusion detection …
and attacks. To combat these threats, the development of effective intrusion detection …
Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN
K Inayah, K Ramli - Jurnal Teknologi Informasi dan Ilmu Komputer, 2024 - jtiik.ub.ac.id
Teknologi dan sistem informasi yang semakin berkembang menjadikan ancaman siber juga
semakin meningkat. Pada tahun 2023, Indonesia menduduki peringkat pertama sebagai …
semakin meningkat. Pada tahun 2023, Indonesia menduduki peringkat pertama sebagai …
Development of Machine Learning Algorithms for Anomaly Detection in Internet of Things (IoT) Networks
V Rith, V Sok, AY Vandika - Journal of Moeslim Research …, 2024 - journal.ypidathu.or.id
The proliferation of Internet of Things (IoT) devices has increased the vulnerability of
networks to security threats, making anomaly detection essential for maintaining system …
networks to security threats, making anomaly detection essential for maintaining system …
Sign Language Detection Using Action Recognition LSTM Deep Learning Model
This project aims to develop a system that can recognize sign language gestures in real-
time using computer vision techniques. The system is designed to bridge the communication …
time using computer vision techniques. The system is designed to bridge the communication …
Evaluating the Effectiveness of the CatBoost Classifier in Distinguishing Benign Traffic, FTP BruteForce and SSH BruteForce Traffic
A Hajjouz, E Avksentieva - 2024 9th International Conference …, 2024 - ieeexplore.ieee.org
In this study, we enhance information security practices by leveraging the CatBoost classifier
within the challenging domain of network intrusion detection. Building upon the foundation …
within the challenging domain of network intrusion detection. Building upon the foundation …
[PDF][PDF] ENHANCING CYBER ATTACK DETECTION IN NETWORK TRAFFIC USING ADAPTIVE REGRESSION TECHNIQUES
LL Scientific - Journal of Theoretical and Applied Information …, 2024 - jatit.org
Cyber attack detection is pivotal for preempting threats, securing data, and safeguarding
critical systems against breaches in our digitally reliant world, ensuring uninterrupted …
critical systems against breaches in our digitally reliant world, ensuring uninterrupted …