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 *

173 related articles for article (PubMed ID: 36992049)

  • 1. An Intelligent Agent-Based Detection System for DDoS Attacks Using Automatic Feature Extraction and Selection.
    Abu Bakar R; Huang X; Javed MS; Hussain S; Majeed MF
    Sensors (Basel); 2023 Mar; 23(6):. PubMed ID: 36992049
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Adaptive Machine Learning Based Distributed Denial-of-Services Attacks Detection and Mitigation System for SDN-Enabled IoT.
    Aslam M; Ye D; Tariq A; Asad M; Hanif M; Ndzi D; Chelloug SA; Elaziz MA; Al-Qaness MAA; Jilani SF
    Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408312
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Distributed Denial of Service Attack Detection in Network Traffic Using Deep Learning Algorithm.
    Ramzan M; Shoaib M; Altaf A; Arshad S; Iqbal F; Castilla ÁK; Ashraf I
    Sensors (Basel); 2023 Oct; 23(20):. PubMed ID: 37896735
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Effective Feature Selection Methods to Detect IoT DDoS Attack in 5G Core Network.
    Kim YE; Kim YS; Kim H
    Sensors (Basel); 2022 May; 22(10):. PubMed ID: 35632228
    [TBL] [Abstract][Full Text] [Related]  

  • 5. SSK-DDoS: distributed stream processing framework based classification system for DDoS attacks.
    Patil NV; Krishna CR; Kumar K
    Cluster Comput; 2022; 25(2):1355-1372. PubMed ID: 35068996
    [TBL] [Abstract][Full Text] [Related]  

  • 6. VMFCVD: An Optimized Framework to Combat Volumetric DDoS Attacks using Machine Learning.
    Prasad A; Chandra S
    Arab J Sci Eng; 2022; 47(8):9965-9983. PubMed ID: 35096507
    [TBL] [Abstract][Full Text] [Related]  

  • 7. A hybrid machine learning approach for detecting unprecedented DDoS attacks.
    Najafimehr M; Zarifzadeh S; Mostafavi S
    J Supercomput; 2022; 78(6):8106-8136. PubMed ID: 35017789
    [TBL] [Abstract][Full Text] [Related]  

  • 8. KS-DDoS: Kafka streams-based classification approach for DDoS attacks.
    Patil NV; Krishna CR; Kumar K
    J Supercomput; 2022; 78(6):8946-8976. PubMed ID: 35068686
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Advanced machine learning approach for DoS attack resilience in internet of vehicles security.
    Ahmed N; Hassan F; Aurangzeb K; Magsi AH; Alhussein M
    Heliyon; 2024 Apr; 10(8):e28844. PubMed ID: 38681562
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A DDoS Detection Method Based on Feature Engineering and Machine Learning in Software-Defined Networks.
    Liu Z; Wang Y; Feng F; Liu Y; Li Z; Shan Y
    Sensors (Basel); 2023 Jul; 23(13):. PubMed ID: 37448025
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Multi-Stage Learning Framework Using Convolutional Neural Network and Decision Tree-Based Classification for Detection of DDoS Pandemic Attacks in SDN-Based SCADA Systems.
    Polat O; Türkoğlu M; Polat H; Oyucu S; Üzen H; Yardımcı F; Aksöz A
    Sensors (Basel); 2024 Feb; 24(3):. PubMed ID: 38339756
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Transport and Application Layer DDoS Attacks Detection to IoT Devices by Using Machine Learning and Deep Learning Models.
    Almaraz-Rivera JG; Perez-Diaz JA; Cantoral-Ceballos JA
    Sensors (Basel); 2022 Apr; 22(9):. PubMed ID: 35591056
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Ensemble Learning Framework for DDoS Detection in SDN-Based SCADA Systems.
    Oyucu S; Polat O; Türkoğlu M; Polat H; Aksöz A; Ağdaş MT
    Sensors (Basel); 2023 Dec; 24(1):. PubMed ID: 38203015
    [TBL] [Abstract][Full Text] [Related]  

  • 14. GLD-Net: Deep Learning to Detect DDoS Attack via Topological and Traffic Feature Fusion.
    Guo W; Qiu H; Liu Z; Zhu J; Wang Q
    Comput Intell Neurosci; 2022; 2022():4611331. PubMed ID: 36017461
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The proposed hybrid deep learning intrusion prediction IoT (HDLIP-IoT) framework.
    Fadel MM; El-Ghamrawy SM; Ali-Eldin AMT; Hassan MK; El-Desoky AI
    PLoS One; 2022; 17(7):e0271436. PubMed ID: 35905101
    [TBL] [Abstract][Full Text] [Related]  

  • 16. IoT-DH dataset for classification, identification, and detection DDoS attack in IoT.
    Saif S; Widyawan W; Ferdiana R
    Data Brief; 2024 Jun; 54():110496. PubMed ID: 38774247
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Countering DDoS Attacks in SIP Based VoIP Networks Using Recurrent Neural Networks.
    Nazih W; Hifny Y; Elkilani WS; Dhahri H; Abdelkader T
    Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33080829
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Error-Robust Distributed Denial of Service Attack Detection Based on an Average Common Feature Extraction Technique.
    Abreu Maranhão JP; Carvalho Lustosa da Costa JP; Pignaton de Freitas E; Javidi E; Timóteo de Sousa Júnior R
    Sensors (Basel); 2020 Oct; 20(20):. PubMed ID: 33081079
    [TBL] [Abstract][Full Text] [Related]  

  • 19. DDoS attack detection in smart grid network using reconstructive machine learning models.
    Naqvi SSA; Li Y; Uzair M
    PeerJ Comput Sci; 2024; 10():e1784. PubMed ID: 38259891
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Conditional Tabular Generative Adversarial Based Intrusion Detection System for Detecting Ddos and Dos Attacks on the Internet of Things Networks.
    Alabsi BA; Anbar M; Rihan SDA
    Sensors (Basel); 2023 Jun; 23(12):. PubMed ID: 37420810
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.