116 related articles for article (PubMed ID: 38894196)
1. CyberSentinel: A Transparent Defense Framework for Malware Detection in High-Stakes Operational Environments.
Basak M; Han MM
Sensors (Basel); 2024 May; 24(11):. PubMed ID: 38894196
[TBL] [Abstract][Full Text] [Related]
2. Deep-Hook: A trusted deep learning-based framework for unknown malware detection and classification in Linux cloud environments.
Landman T; Nissim N
Neural Netw; 2021 Dec; 144():648-685. PubMed ID: 34656885
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Explainable Malware Detection System Using Transformers-Based Transfer Learning and Multi-Model Visual Representation.
Ullah F; Alsirhani A; Alshahrani MM; Alomari A; Naeem H; Shah SA
Sensors (Basel); 2022 Sep; 22(18):. PubMed ID: 36146112
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. GSB: GNGS and SAG-BiGRU network for malware dynamic detection.
Hu Z; Liu G; Xiang X; Li Y; Zhuang S
PLoS One; 2024; 19(4):e0298809. PubMed ID: 38635682
[TBL] [Abstract][Full Text] [Related]
7. Malware homology determination using visualized images and feature fusion.
Zhu X; Huang J; Wang B; Qi C
PeerJ Comput Sci; 2021; 7():e494. PubMed ID: 33977134
[TBL] [Abstract][Full Text] [Related]
8. Channel Features and API Frequency-Based Transformer Model for Malware Identification.
Qian L; Cong L
Sensors (Basel); 2024 Jan; 24(2):. PubMed ID: 38257673
[TBL] [Abstract][Full Text] [Related]
9. A malware detection system using a hybrid approach of multi-heads attention-based control flow traces and image visualization.
Ullah F; Srivastava G; Ullah S
J Cloud Comput (Heidelb); 2022; 11(1):75. PubMed ID: 36345308
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. 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]
13. 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]
14. Cyber Code Intelligence for Android Malware Detection.
Qiu J; Han QL; Luo W; Pan L; Nepal S; Zhang J; Xiang Y
IEEE Trans Cybern; 2023 Jan; 53(1):617-627. PubMed ID: 35476561
[TBL] [Abstract][Full Text] [Related]
15. FedHGCDroid: An Adaptive Multi-Dimensional Federated Learning for Privacy-Preserving Android Malware Classification.
Jiang C; Yin K; Xia C; Huang W
Entropy (Basel); 2022 Jul; 24(7):. PubMed ID: 35885142
[TBL] [Abstract][Full Text] [Related]
16. Artificial intelligence-driven malware detection framework for internet of things environment.
Alsubai S; Dutta AK; Alnajim AM; Wahab Sait AR; Ayub R; AlShehri AM; Ahmad N
PeerJ Comput Sci; 2023; 9():e1366. PubMed ID: 37346520
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Malware detection based on semi-supervised learning with malware visualization.
Gao T; Zhao L; Li X; Chen W
Math Biosci Eng; 2021 Jul; 18(5):5995-6011. PubMed ID: 34517520
[TBL] [Abstract][Full Text] [Related]
19. BejaGNN: behavior-based Java malware detection via graph neural network.
Feng P; Yang L; Lu D; Xi N; Ma J
J Supercomput; 2023 Apr; ():1-25. PubMed ID: 37359339
[TBL] [Abstract][Full Text] [Related]
20. A Novel Detection and Multi-Classification Approach for IoT-Malware Using Random Forest Voting of Fine-Tuning Convolutional Neural Networks.
Ben Atitallah S; Driss M; Almomani I
Sensors (Basel); 2022 Jun; 22(11):. PubMed ID: 35684922
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
