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 *

143 related articles for article (PubMed ID: 36850815)

  • 1. APT Attack Detection Scheme Based on CK Sketch and DNS Traffic.
    Xue D; Chi Y; Wu B; Zhao L
    Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850815
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Discovering Suspicious APT Behaviors by Analyzing DNS Activities.
    Yan G; Li Q; Guo D; Meng X
    Sensors (Basel); 2020 Jan; 20(3):. PubMed ID: 32013016
    [TBL] [Abstract][Full Text] [Related]  

  • 3. AULD: Large Scale Suspicious DNS Activities Detection via Unsupervised Learning in Advanced Persistent Threats.
    Yan G; Li Q; Guo D; Li B
    Sensors (Basel); 2019 Jul; 19(14):. PubMed ID: 31330986
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Intelligent model for the detection and classification of encrypted network traffic in cloud infrastructure.
    Dawood M; Xiao C; Tu S; Alotaibi FA; Alnfiai MM; Farhan M
    PeerJ Comput Sci; 2024; 10():e2027. PubMed ID: 38855228
    [TBL] [Abstract][Full Text] [Related]  

  • 5. A novel approach for APT attack detection based on an advanced computing.
    Xuan CD; Nguyen TT
    Sci Rep; 2024 Sep; 14(1):22223. PubMed ID: 39333649
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. Hybrid rule-based botnet detection approach using machine learning for analysing DNS traffic.
    Al-Mashhadi S; Anbar M; Hasbullah I; Alamiedy TA
    PeerJ Comput Sci; 2021; 7():e640. PubMed ID: 34458571
    [TBL] [Abstract][Full Text] [Related]  

  • 8. A novel approach for APT attack detection based on feature intelligent extraction and representation learning.
    Do Xuan C; Cuong NH
    PLoS One; 2024; 19(6):e0305618. PubMed ID: 38913651
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Detection of Middlebox-Based Attacks in Healthcare Internet of Things Using Multiple Machine Learning Models.
    Al Abdulwahid A
    Comput Intell Neurosci; 2022; 2022():2037954. PubMed ID: 36479020
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Mining IP to Domain Name Interactions to Detect DNS Flood Attacks on Recursive DNS Servers.
    Alonso R; Monroy R; Trejo LA
    Sensors (Basel); 2016 Aug; 16(8):. PubMed ID: 27548169
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. A systematic literature review for APT detection and Effective Cyber Situational Awareness (ECSA) conceptual model.
    Salim DT; Singh MM; Keikhosrokiani P
    Heliyon; 2023 Jul; 9(7):e17156. PubMed ID: 37449192
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Lightweight Double-Stage Scheme to Identify Malicious DNS over HTTPS Traffic Using a Hybrid Learning Approach.
    Abu Al-Haija Q; Alohaly M; Odeh A
    Sensors (Basel); 2023 Mar; 23(7):. PubMed ID: 37050549
    [TBL] [Abstract][Full Text] [Related]  

  • 14. GSOOA-1DDRSN: Network traffic anomaly detection based on deep residual shrinkage networks.
    Zuo F; Zhang D; Li L; He Q; Deng J
    Heliyon; 2024 Jun; 10(11):e32087. PubMed ID: 38868050
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Data-Driven Network Analysis for Anomaly Traffic Detection.
    Alam S; Alam Y; Cui S; Akujuobi C
    Sensors (Basel); 2023 Sep; 23(19):. PubMed ID: 37837004
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 17. 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]  

  • 18. Flow-Data Gathering Using NetFlow Sensors for Fitting Malicious-Traffic Detection Models.
    Campazas-Vega A; Crespo-Martínez IS; Guerrero-Higueras ÁM; Fernández-Llamas C
    Sensors (Basel); 2020 Dec; 20(24):. PubMed ID: 33353086
    [TBL] [Abstract][Full Text] [Related]  

  • 19. 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]  

  • 20. Network Anomaly Intrusion Detection Based on Deep Learning Approach.
    Wang YC; Houng YC; Chen HX; Tseng SM
    Sensors (Basel); 2023 Feb; 23(4):. PubMed ID: 36850768
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.