205 related articles for article (PubMed ID: 36679406)
1. 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]
2. Detection of Android Malware in the Internet of Things through the K-Nearest Neighbor Algorithm.
Babbar H; Rani S; Sah DK; AlQahtani SA; Kashif Bashir A
Sensors (Basel); 2023 Aug; 23(16):. PubMed ID: 37631793
[TBL] [Abstract][Full Text] [Related]
3. ZeVigilante: Detecting Zero-Day Malware Using Machine Learning and Sandboxing Analysis Techniques.
Alhaidari F; Shaib NA; Alsafi M; Alharbi H; Alawami M; Aljindan R; Rahman AU; Zagrouba R
Comput Intell Neurosci; 2022; 2022():1615528. PubMed ID: 35586085
[TBL] [Abstract][Full Text] [Related]
4. TKRD: Trusted kernel rootkit detection for cybersecurity of VMs based on machine learning and memory forensic analysis.
Wang X; Zhang JB; Zhang A; Ren JC
Math Biosci Eng; 2019 Mar; 16(4):2650-2667. PubMed ID: 31137231
[TBL] [Abstract][Full Text] [Related]
5. Evaluation of Machine Learning Algorithms for Malware Detection.
Akhtar MS; Feng T
Sensors (Basel); 2023 Jan; 23(2):. PubMed ID: 36679741
[TBL] [Abstract][Full Text] [Related]
6. Windows malware detection based on static analysis with multiple features.
Yousuf MI; Anwer I; Riasat A; Zia KT; Kim S
PeerJ Comput Sci; 2023; 9():e1319. PubMed ID: 37346681
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. On Detecting Cryptojacking on Websites: Revisiting the Use of Classifiers.
Aponte-Novoa FA; Povedano Álvarez D; Villanueva-Polanco R; Sandoval Orozco AL; García Villalba LJ
Sensors (Basel); 2022 Nov; 22(23):. PubMed ID: 36501921
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. Artificial Intelligence Algorithms for Malware Detection in Android-Operated Mobile Devices.
Alkahtani H; Aldhyani THH
Sensors (Basel); 2022 Mar; 22(6):. PubMed ID: 35336437
[TBL] [Abstract][Full Text] [Related]
11. A Kullback-Liebler divergence-based representation algorithm for malware detection.
Aboaoja FA; Zainal A; Ghaleb FA; Alghamdi NS; Saeed F; Alhuwayji H
PeerJ Comput Sci; 2023; 9():e1492. PubMed ID: 37810364
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. MFDroid: A Stacking Ensemble Learning Framework for Android Malware Detection.
Wang X; Zhang L; Zhao K; Ding X; Yu M
Sensors (Basel); 2022 Mar; 22(7):. PubMed ID: 35408211
[TBL] [Abstract][Full Text] [Related]
15. A Hybrid Analysis-Based Approach to Android Malware Family Classification.
Ding C; Luktarhan N; Lu B; Zhang W
Entropy (Basel); 2021 Aug; 23(8):. PubMed ID: 34441149
[TBL] [Abstract][Full Text] [Related]
16. A detection method for android application security based on TF-IDF and machine learning.
Yuan H; Tang Y; Sun W; Liu L
PLoS One; 2020; 15(9):e0238694. PubMed ID: 32915836
[TBL] [Abstract][Full Text] [Related]
17. Enhancing Cyber-Resilience for Small and Medium-Sized Organizations with Prescriptive Malware Analysis, Detection and Response.
Ilca LF; Lucian OP; Balan TC
Sensors (Basel); 2023 Jul; 23(15):. PubMed ID: 37571540
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Analyzing and comparing the effectiveness of malware detection: A study of machine learning approaches.
Azeem M; Khan D; Iftikhar S; Bawazeer S; Alzahrani M
Heliyon; 2024 Jan; 10(1):e23574. PubMed ID: 38187275
[TBL] [Abstract][Full Text] [Related]
20. On the classification of Microsoft-Windows ransomware using hardware profile.
Aurangzeb S; Rais RNB; Aleem M; Islam MA; Iqbal MA
PeerJ Comput Sci; 2021; 7():e361. PubMed ID: 33817011
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
