161 related articles for article (PubMed ID: 32685709)
1. Comprehensive analysis and recommendation of feature evaluation measures for intrusion detection.
Binbusayyis A; Vaiyapuri T
Heliyon; 2020 Jul; 6(7):e04262. PubMed ID: 32685709
[TBL] [Abstract][Full Text] [Related]
2. A hybrid feature weighted attention based deep learning approach for an intrusion detection system using the random forest algorithm.
Hashmi A; Barukab OM; Hamza Osman A
PLoS One; 2024; 19(5):e0302294. PubMed ID: 38781186
[TBL] [Abstract][Full Text] [Related]
3. Multi-Classification and Tree-Based Ensemble Network for the Intrusion Detection System in the Internet of Vehicles.
Gou W; Zhang H; Zhang R
Sensors (Basel); 2023 Oct; 23(21):. PubMed ID: 37960485
[TBL] [Abstract][Full Text] [Related]
4. The Use of Ensemble Models for Multiple Class and Binary Class Classification for Improving Intrusion Detection Systems.
Iwendi C; Khan S; Anajemba JH; Mittal M; Alenezi M; Alazab M
Sensors (Basel); 2020 Apr; 20(9):. PubMed ID: 32365937
[TBL] [Abstract][Full Text] [Related]
5. Application of deep autoencoder as an one-class classifier for unsupervised network intrusion detection: a comparative evaluation.
Vaiyapuri T; Binbusayyis A
PeerJ Comput Sci; 2020; 6():e327. PubMed ID: 33816977
[TBL] [Abstract][Full Text] [Related]
6. A Novel Feature-Selection Algorithm in IoT Networks for Intrusion Detection.
Nazir A; Memon Z; Sadiq T; Rahman H; Khan IU
Sensors (Basel); 2023 Sep; 23(19):. PubMed ID: 37836983
[TBL] [Abstract][Full Text] [Related]
7. A Hybrid Spectral Clustering and Deep Neural Network Ensemble Algorithm for Intrusion Detection in Sensor Networks.
Ma T; Wang F; Cheng J; Yu Y; Chen X
Sensors (Basel); 2016 Oct; 16(10):. PubMed ID: 27754380
[TBL] [Abstract][Full Text] [Related]
8. Adaptive Anomaly Detection Framework Model Objects in Cyberspace.
Alkahtani H; Aldhyani THH; Al-Yaari M
Appl Bionics Biomech; 2020; 2020():6660489. PubMed ID: 33376505
[TBL] [Abstract][Full Text] [Related]
9. Improving the Classification Effectiveness of Intrusion Detection by Using Improved Conditional Variational AutoEncoder and Deep Neural Network.
Yang Y; Zheng K; Wu C; Yang Y
Sensors (Basel); 2019 Jun; 19(11):. PubMed ID: 31159512
[TBL] [Abstract][Full Text] [Related]
10. Anomaly Detection IDS for Detecting DoS Attacks in IoT Networks Based on Machine Learning Algorithms.
Altulaihan E; Almaiah MA; Aljughaiman A
Sensors (Basel); 2024 Jan; 24(2):. PubMed ID: 38276404
[TBL] [Abstract][Full Text] [Related]
11. Enhancing Network Intrusion Detection Using an Ensemble Voting Classifier for Internet of Things.
Farooqi AH; Akhtar S; Rahman H; Sadiq T; Abbass W
Sensors (Basel); 2023 Dec; 24(1):. PubMed ID: 38202990
[TBL] [Abstract][Full Text] [Related]
12. ROAST-IoT: A Novel Range-Optimized Attention Convolutional Scattered Technique for Intrusion Detection in IoT Networks.
Mahalingam A; Perumal G; Subburayalu G; Albathan M; Altameem A; Almakki RS; Hussain A; Abbas Q
Sensors (Basel); 2023 Sep; 23(19):. PubMed ID: 37836874
[TBL] [Abstract][Full Text] [Related]
13. Logistic Regression Ensemble Classifier for Intrusion Detection System in Internet of Things.
Chalichalamala S; Govindan N; Kasarapu R
Sensors (Basel); 2023 Dec; 23(23):. PubMed ID: 38067959
[TBL] [Abstract][Full Text] [Related]
14. Intrusion Detection System Using Deep Neural Network for In-Vehicle Network Security.
Kang MJ; Kang JW
PLoS One; 2016; 11(6):e0155781. PubMed ID: 27271802
[TBL] [Abstract][Full Text] [Related]
15. A robust intrusion detection system based on a shallow learning model and feature extraction techniques.
E L Asry C; Benchaji I; Douzi S; E L Ouahidi B
PLoS One; 2024; 19(1):e0295801. PubMed ID: 38266011
[TBL] [Abstract][Full Text] [Related]
16. An ensemble learning based IDS using Voting rule: VEL-IDS.
Emanet S; Karatas Baydogmus G; Demir O
PeerJ Comput Sci; 2023; 9():e1553. PubMed ID: 37810337
[TBL] [Abstract][Full Text] [Related]
17. In-vehicle network intrusion detection systems: a systematic survey of deep learning-based approaches.
Luo F; Wang J; Zhang X; Jiang Y; Li Z; Luo C
PeerJ Comput Sci; 2023; 9():e1648. PubMed ID: 38077582
[TBL] [Abstract][Full Text] [Related]
18. Data Randomization and Cluster-Based Partitioning for Botnet Intrusion Detection.
Al-Jarrah OY; Alhussein O; Yoo PD; Muhaidat S; Taha K; Kim K
IEEE Trans Cybern; 2016 Aug; 46(8):1796-806. PubMed ID: 26540724
[TBL] [Abstract][Full Text] [Related]
19. Intrusion Detection System in the Advanced Metering Infrastructure: A Cross-Layer Feature-Fusion CNN-LSTM-Based Approach.
Yao R; Wang N; Liu Z; Chen P; Sheng X
Sensors (Basel); 2021 Jan; 21(2):. PubMed ID: 33477451
[TBL] [Abstract][Full Text] [Related]
20. Fusion of Heterogeneous Intrusion Detection Systems for Network Attack Detection.
Kaliappan J; Thiagarajan R; Sundararajan K
ScientificWorldJournal; 2015; 2015():314601. PubMed ID: 26295058
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]