Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Kehinde O. Babaagba"'
Publikováno v:
International Journal of Intelligent Systems. 37:7058-7078
Internet of Things (IoT) is fast growing. Non-PC devices under the umbrella of IoT have been increasingly applied in various fields and will soon account for a significant share of total Internet traffic. However, the security and privacy of IoT and
Autor:
Kehinde O. Babaagba, Mayowa Ayodele
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783031302282
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f57c525183636548f08b03eb03ef009e
https://doi.org/10.1007/978-3-031-30229-9_11
https://doi.org/10.1007/978-3-031-30229-9_11
Publikováno v:
2022 IEEE Conference on Dependable and Secure Computing (DSC).
Publikováno v:
CEC
Detecting metamorphic malware provides a challenge to machine-learning models as trained models might not generalise to future mutant variants of the malware. To address this, we explore whether machine-learning models can be improved by augmenting t
Publikováno v:
Applications of Evolutionary Computation ISBN: 9783030437213
EvoApplications
EvoApplications
In the field of metamorphic malware detection, training a detection model with malware samples that reflect potential mutants of the malware is crucial in developing a model resistant to future attacks. In this paper, we use a Multi-dimensional Archi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ef154fce55c3ee4c1cb8c6355587c7d8
https://doi.org/10.1007/978-3-030-43722-0_8
https://doi.org/10.1007/978-3-030-43722-0_8
Publikováno v:
Proceedings of the 2019 8th International Conference on Educational and Information Technology.
In this paper, the effect of feature selection in malware detection using machine learning techniques is studied. We employ supervised and unsupervised machine learning algorithms with and without feature selection. These include both classification
Publikováno v:
Communications in Computer and Information Science ISBN: 9789811513039
DependSys
DependSys
The ability to detect metamorphic malware has generated significant research interest over recent years, particularly given its proliferation on mobile devices. Such malware is particularly hard to detect via signature-based intrusion detection syste
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1890a92189dc894efc1b1f397ad9f630
https://doi.org/10.1007/978-981-15-1304-6_29
https://doi.org/10.1007/978-981-15-1304-6_29