These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

465 related articles for article (PubMed ID: 35111914)

  • 1. Network intrusion detection using oversampling technique and machine learning algorithms.
    Ahmed HA; Hameed A; Bawany NZ
    PeerJ Comput Sci; 2022; 8():e820. PubMed ID: 35111914
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Improving the Performance of Machine Learning-Based Network Intrusion Detection Systems on the UNSW-NB15 Dataset.
    Moualla S; Khorzom K; Jafar A
    Comput Intell Neurosci; 2021; 2021():5557577. PubMed ID: 34220999
    [TBL] [Abstract][Full Text] [Related]  

  • 3. 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]  

  • 4. Artificial Intelligence Algorithm-Based Economic Denial of Sustainability Attack Detection Systems: Cloud Computing Environments.
    Aldhyani THH; Alkahtani H
    Sensors (Basel); 2022 Jun; 22(13):. PubMed ID: 35808184
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Evaluation of Machine Learning Techniques for Traffic Flow-Based Intrusion Detection.
    Rodríguez M; Alesanco Á; Mehavilla L; García J
    Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36502028
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Wireless Sensor Networks Intrusion Detection Based on SMOTE and the Random Forest Algorithm.
    Tan X; Su S; Huang Z; Guo X; Zuo Z; Sun X; Li L
    Sensors (Basel); 2019 Jan; 19(1):. PubMed ID: 30626020
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Adversarial attacks against supervised machine learning based network intrusion detection systems.
    Alshahrani E; Alghazzawi D; Alotaibi R; Rabie O
    PLoS One; 2022; 17(10):e0275971. PubMed ID: 36240162
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. Classification model for accuracy and intrusion detection using machine learning approach.
    Agarwal A; Sharma P; Alshehri M; Mohamed AA; Alfarraj O
    PeerJ Comput Sci; 2021; 7():e437. PubMed ID: 33954233
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Botnet Attack Detection in IoT Using Machine Learning.
    Alissa K; Alyas T; Zafar K; Abbas Q; Tabassum N; Sakib S
    Comput Intell Neurosci; 2022; 2022():4515642. PubMed ID: 36238679
    [TBL] [Abstract][Full Text] [Related]  

  • 11. An Imbalanced Generative Adversarial Network-Based Approach for Network Intrusion Detection in an Imbalanced Dataset.
    Rao YN; Suresh Babu K
    Sensors (Basel); 2023 Jan; 23(1):. PubMed ID: 36617148
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A novel intrusion detection framework for optimizing IoT security.
    Qaddos A; Yaseen MU; Al-Shamayleh AS; Imran M; Akhunzada A; Alharthi SZ
    Sci Rep; 2024 Sep; 14(1):21789. PubMed ID: 39294195
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Using Machine Learning Multiclass Classification Technique to Detect IoT Attacks in Real Time.
    Alrefaei A; Ilyas M
    Sensors (Basel); 2024 Jul; 24(14):. PubMed ID: 39065914
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Attack-Aware IoT Network Traffic Routing Leveraging Ensemble Learning.
    Abu Al-Haija Q; Al-Badawi A
    Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009784
    [TBL] [Abstract][Full Text] [Related]  

  • 15. 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]  

  • 16. Dynamic Data Infrastructure Security for Interoperable e-Healthcare Systems: A Semantic Feature-Driven NoSQL Intrusion Attack Detection Model.
    Sreejith R; Senthil S
    Biomed Res Int; 2022; 2022():4080199. PubMed ID: 35722459
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Cyber Attack Detection for Self-Driving Vehicle Networks Using Deep Autoencoder Algorithms.
    Alsaade FW; Al-Adhaileh MH
    Sensors (Basel); 2023 Apr; 23(8):. PubMed ID: 37112429
    [TBL] [Abstract][Full Text] [Related]  

  • 19. SMOTE-DRNN: A Deep Learning Algorithm for Botnet Detection in the Internet-of-Things Networks.
    Popoola SI; Adebisi B; Ande R; Hammoudeh M; Anoh K; Atayero AA
    Sensors (Basel); 2021 Apr; 21(9):. PubMed ID: 33923151
    [TBL] [Abstract][Full Text] [Related]  

  • 20. STB: synthetic minority oversampling technique for tree-boosting models for imbalanced datasets of intrusion detection systems.
    Li LH; Ahmad R; Tanone R; Sharma AK
    PeerJ Comput Sci; 2023; 9():e1580. PubMed ID: 38077567
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 24.