BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

133 related articles for article (PubMed ID: 32324836)

  • 21. An Efficient DenseNet-Based Deep Learning Model for Malware Detection.
    Hemalatha J; Roseline SA; Geetha S; Kadry S; Damaševičius R
    Entropy (Basel); 2021 Mar; 23(3):. PubMed ID: 33804035
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Cyber-Threat Detection System Using a Hybrid Approach of Transfer Learning and Multi-Model Image Representation.
    Ullah F; Ullah S; Naeem MR; Mostarda L; Rho S; Cheng X
    Sensors (Basel); 2022 Aug; 22(15):. PubMed ID: 35957440
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Malicious Code Variant Identification Based on Multiscale Feature Fusion CNNs.
    Wang S; Wang J; Song Y; Li S
    Comput Intell Neurosci; 2021; 2021():1070586. PubMed ID: 34950195
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A Study on the Application of Distributed System Technology-Guided Machine Learning in Malware Detection.
    Jin S; Guo Z; Liu D; Yang Y
    Comput Intell Neurosci; 2022; 2022():4977898. PubMed ID: 35251151
    [TBL] [Abstract][Full Text] [Related]  

  • 25. An Efficient CNN-Based Deep Learning Model to Detect Malware Attacks (CNN-DMA) in 5G-IoT Healthcare Applications.
    Anand A; Rani S; Anand D; Aljahdali HM; Kerr D
    Sensors (Basel); 2021 Sep; 21(19):. PubMed ID: 34640666
    [TBL] [Abstract][Full Text] [Related]  

  • 26. PermDroid a framework developed using proposed feature selection approach and machine learning techniques for Android malware detection.
    Mahindru A; Arora H; Kumar A; Gupta SK; Mahajan S; Kadry S; Kim J
    Sci Rep; 2024 May; 14(1):10724. PubMed ID: 38730228
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Perturbing BEAMs: EEG adversarial attack to deep learning models for epilepsy diagnosing.
    Yu J; Qiu K; Wang P; Su C; Fan Y; Cao Y
    BMC Med Inform Decis Mak; 2023 Jul; 23(1):115. PubMed ID: 37415186
    [TBL] [Abstract][Full Text] [Related]  

  • 28. An Insight into the Machine-Learning-Based Fileless Malware Detection.
    Khalid O; Ullah S; Ahmad T; Saeed S; Alabbad DA; Aslam M; Buriro A; Ahmad R
    Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679406
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Adversarial Robustness of Deep Reinforcement Learning Based Dynamic Recommender Systems.
    Wang S; Cao Y; Chen X; Yao L; Wang X; Sheng QZ
    Front Big Data; 2022; 5():822783. PubMed ID: 35592793
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Explainable Artificial Intelligence-Based IoT Device Malware Detection Mechanism Using Image Visualization and Fine-Tuned CNN-Based Transfer Learning Model.
    Naeem H; Alshammari BM; Ullah F
    Comput Intell Neurosci; 2022; 2022():7671967. PubMed ID: 35875737
    [TBL] [Abstract][Full Text] [Related]  

  • 31. An Attribute Extraction for Automated Malware Attack Classification and Detection Using Soft Computing Techniques.
    Albishry N; AlGhamdi R; Almalawi A; Khan AI; Kshirsagar PR; BaruDebtera
    Comput Intell Neurosci; 2022; 2022():5061059. PubMed ID: 35510059
    [TBL] [Abstract][Full Text] [Related]  

  • 32. A static analysis approach for Android permission-based malware detection systems.
    Mohamad Arif J; Ab Razak MF; Awang S; Tuan Mat SR; Ismail NSN; Firdaus A
    PLoS One; 2021; 16(9):e0257968. PubMed ID: 34591930
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Malware Detection in Internet of Things (IoT) Devices Using Deep Learning.
    Riaz S; Latif S; Usman SM; Ullah SS; Algarni AD; Yasin A; Anwar A; Elmannai H; Hussain S
    Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36502007
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Randomized Prediction Games for Adversarial Machine Learning.
    Rota Bulo S; Biggio B; Pillai I; Pelillo M; Roli F
    IEEE Trans Neural Netw Learn Syst; 2017 Nov; 28(11):2466-2478. PubMed ID: 27514067
    [TBL] [Abstract][Full Text] [Related]  

  • 35. FILM: Filtering and Machine Learning for Malware Detection in Edge Computing.
    Kim YJ; Park CH; Yoon M
    Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336322
    [TBL] [Abstract][Full Text] [Related]  

  • 36. E2E-RDS: Efficient End-to-End Ransomware Detection System Based on Static-Based ML and Vision-Based DL Approaches.
    Almomani I; Alkhayer A; El-Shafai W
    Sensors (Basel); 2023 May; 23(9):. PubMed ID: 37177671
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Evaluation of Malware Classification Models for Heterogeneous Data.
    Bae H
    Sensors (Basel); 2024 Jan; 24(1):. PubMed ID: 38203154
    [TBL] [Abstract][Full Text] [Related]  

  • 38. On the Performance of Generative Adversarial Network by Limiting Mode Collapse for Malware Detection Systems.
    Murray A; Rawat DB
    Sensors (Basel); 2021 Dec; 22(1):. PubMed ID: 35009810
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Digital Forensics for Malware Classification: An Approach for Binary Code to Pixel Vector Transition.
    Naeem MR; Amin R; Alshamrani SS; Alshehri A
    Comput Intell Neurosci; 2022; 2022():6294058. PubMed ID: 35498213
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Transfer Learning for Image-Based Malware Detection for IoT.
    Panda P; C U OK; Marappan S; Ma S; S M; Veesani Nandi D
    Sensors (Basel); 2023 Mar; 23(6):. PubMed ID: 36991965
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.