Incremental Adversarial Learning for Polymorphic Attack Detection
U Sabeel, SS Heydari, K El-Khatib… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
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 …
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 …
Sign Language Detection Using Action Recognition LSTM Deep Learning Model
N Snehalatha, SM Kumar, H Kavitha… - 2024 Second …, 2024 - ieeexplore.ieee.org
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 …
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 …
[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 …
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 …
Comparison of Convolutional Neural Networks, Long Short-Term Memory networks, and Recurrent Neural Networks for Intrusion Detection System
EC Uwazie, IS Iheonkhan… - … and Business for …, 2024 - ieeexplore.ieee.org
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 …