过去一年中添加的文章，按日期排序
[HTML][HTML] A hybrid approach for efficient feature selection in anomaly intrusion detection for IoT networks
29 天前 - … approach using multiple machine learning algorithms, … We use three benchmark
datasets such as BoT-IoT, TON-… the field of attack detection and feature selection, providing an …
datasets such as BoT-IoT, TON-… the field of attack detection and feature selection, providing an …
A Hybrid Feature Selection Model for Anomaly-Based Intrusion Detection in IoT Networks
67 天前 - … machine learning, this paper aims to develop a new feature … algorithm to detect
the attack by binary classification … on the NSL-KDD and BoT-IoT datasets. DT achieved high …
the attack by binary classification … on the NSL-KDD and BoT-IoT datasets. DT achieved high …
Strengthening Cybersecurity using a Hybrid Classification Model with SCO Optimization for Enhanced Network Intrusion Detection System
SEVS Pillai, R Vallabhaneni… - 2024 International …, 2024 - ieeexplore.ieee.org
196 天前 - … detection system (IDS) that makes use of deep learning. … and identify malicious
attacks in network traffic. Using multi-… This research makes use of the BoT-IoT [20] dataset. The …
attacks in network traffic. Using multi-… This research makes use of the BoT-IoT [20] dataset. The …
Cyber Security Intrusion Detection and Bot Data Collection using Deep Learning in the IoT.
FA Alotaibi, S Mishra - International Journal of Advanced …, 2024 - search.ebscohost.com
210 天前 - … -attack detection … selection metric and an algorithm to filter features accurately.
The procedure is assessed using the dataset of the Bot-IoT and four different machine learning …
The procedure is assessed using the dataset of the Bot-IoT and four different machine learning …
Modified genetic algorithm and fine-tuned long short-term memory network for intrusion detection in the internet of things networks with edge capabilities
YK Saheed, OH Abdulganiyu, TA Tchakoucht - Applied Soft Computing, 2024 - Elsevier
212 天前 - … 0.68, and training time of 81.3 seconds on BoT-IoT. The proposed … on edge servers
to detect cyber-attacks in real-time, … -LSTM machine learning models to promptly identify and …
to detect cyber-attacks in real-time, … -LSTM machine learning models to promptly identify and …
Cybersecurity Using Hybrid Type Model for Classification Through SCO Optimization Technique
231 天前 - … An IDS that uses deep learning is described in this paper. … service attacks were all
part of the multiclassification testing… This research makes use of the BoT-IoT [22] dataset. The …
part of the multiclassification testing… This research makes use of the BoT-IoT [22] dataset. The …
Fractional hunger jellyfish search optimization based deep quantum neural network for malicious traffic segregation and attack detection
270 天前 - … based on a hybrid optimization-enabled deep learning (DL… the NSL-KDD dataset
and BoT-IoT dataset. The proposed … exclusive of jellyfish u is selected randomly. Hence, every …
and BoT-IoT dataset. The proposed … exclusive of jellyfish u is selected randomly. Hence, every …