Zobrazeno 1 - 8
of 8
pro vyhledávání: '"S. L. Shiva Darshan"'
Publikováno v:
In Procedia Computer Science 2024 235:2486-2497
Autor:
Akashraj Raga, Achyuth Nag, B Rahul Reddy, Dhanush D Shetty, B S Prashanth, M V Manoj Kumar, S L Shiva Darshan
Publikováno v:
2021 International Conference on Forensics, Analytics, Big Data, Security (FABS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::25689659753c3bf3c1965780e59a0e3d
https://doi.org/10.1109/fabs52071.2021.9702606
https://doi.org/10.1109/fabs52071.2021.9702606
Autor:
S. Ashok Kumar, Aakash S. Shetty, S. L. Shiva Darshan, Bishav Mohan, Roshan Fernandes, Abdul Mueez
Publikováno v:
Emerging Research in Computing, Information, Communication and Applications ISBN: 9789811613418
Emerging Research in Computing, Information, Communication and Applications
Emerging Research in Computing, Information, Communication and Applications
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ee3cb6ddecf15108f91b5a34727efdfb
https://doi.org/10.1007/978-981-16-1342-5_33
https://doi.org/10.1007/978-981-16-1342-5_33
Autor:
C. D. Jaidhar, S. L. Shiva Darshan
Publikováno v:
International Journal of Machine Learning and Cybernetics. 11:339-358
The emergence of advanced malware is a serious threat to information security. A prominent technique that identifies sophisticated malware should consider the runtime behaviour of the source file to detect malicious intent. Although the behaviour-bas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::036627d574352d43b7032af60eb6fd19
https://doi.org/10.1007/s13042-019-00978-7
https://doi.org/10.1007/s13042-019-00978-7
Autor:
C. D. Jaidhar, S. L. Shiva Darshan
Publikováno v:
Journal of Computer Virology and Hacking Techniques. 15:127-146
To combat exponentially evolved modern malware, an effective Malware Detection System and precise malware classification is highly essential. In this paper, the Linear Support Vector Classification (LSVC) recommended Hybrid Features based Malware Det
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4db190cc28300998a9c9f1fb3cfab886
https://doi.org/10.1007/s11416-018-0327-9
https://doi.org/10.1007/s11416-018-0327-9
Autor:
C. D. Jaidhar, S. L. Shiva Darshan
Publikováno v:
Procedia Computer Science. 125:346-356
The dimensionality of the feature space exhibits a significant effect on the processing time and predictive performance of the Malware Detection Systems (MDS). Therefore, the selection of relevant features is crucial for the classification process. F
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::af38bd2ed91ac3e38613e808ab5e6eef
https://doi.org/10.1016/j.procs.2017.12.046
https://doi.org/10.1016/j.procs.2017.12.046
Publikováno v:
2017 ISEA Asia Security and Privacy (ISEASP).
Currently, the Internet faces serious threat from malwares, and its propagation may cause great havoc on computers and network security solutions. Several existing anti-malware defensive solutions detect known malware accurately. However, they fail t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed9f52faef0e22624f28c08cf432315e
https://doi.org/10.1109/iseasp.2017.7976984
https://doi.org/10.1109/iseasp.2017.7976984
Publikováno v:
ICIIS
Malicious software or malware has grown rapidly and many anti-malware defensive solutions have failed to detect the unknown malware since most of them rely on signature-based technique. This technique can detect a malware based on a pre-defined signa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc274547b2a50cbda9bae35453d62f68
https://doi.org/10.1109/iciinfs.2016.8262998
https://doi.org/10.1109/iciinfs.2016.8262998