Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Mohamad Nizam Kassim"'
Publikováno v:
2022 International Conference on Cyber Resilience (ICCR).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5720859da4362f6d0d69fdfbc0f30cb
https://doi.org/10.1109/iccr56254.2022.9995764
https://doi.org/10.1109/iccr56254.2022.9995764
Publikováno v:
2022 International Conference on Data Science and Its Applications (ICoDSA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9851b1c5497bc7c7e6b834a083a4fa52
https://doi.org/10.1109/icodsa55874.2022.9862930
https://doi.org/10.1109/icodsa55874.2022.9862930
Autor:
Nurulmanja Atiqah Maliki, Anazida Zainal, Fuad Abdulgaleel Abdoh Ghaleb, Mohamad Nizam Kassim
Publikováno v:
2021 International Conference on Data Science and Its Applications (ICoDSA).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::33bd67cdcafcd6a868353551b8985764
https://doi.org/10.1109/icodsa53588.2021.9617493
https://doi.org/10.1109/icodsa53588.2021.9617493
Publikováno v:
Advances in Intelligent Systems and Computing ISBN: 9783030493448
SoCPaR
SoCPaR
Recently, the emergence of the new malware has caused a major threat especially in finance sector in which many of the online banking data was stolen by the adversaries. The malware threats information needs to be collected immediately after its outb
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::071ac8555a05677f59b9bec6636de521
https://doi.org/10.1007/978-3-030-49345-5_14
https://doi.org/10.1007/978-3-030-49345-5_14
Publikováno v:
Advanced Science Letters. 24:8483-8487
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4023b4c82a1dc7ce6e8340eb6c78ac23
https://doi.org/10.1166/asl.2018.12594
https://doi.org/10.1166/asl.2018.12594
Autor:
Mohd Aizaini Maarof, Amirudin Abdul Wahab, Anazida Zainal, Shaiful Hisham Mat Jali, Mohamad Nizam Kassim
Publikováno v:
Smart Innovation, Systems and Technologies ISBN: 9789811500763
In general, the current text stemmers for Malay texts were not developed for text stemming against social media texts. Therefore, there is a need to develop an enhanced text stemmer that is able to map morphological variants based on the characterist
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::98848d1c70f5e50366e722094677e0ce
https://doi.org/10.1007/978-981-15-0077-0_44
https://doi.org/10.1007/978-981-15-0077-0_44
Autor:
Amirudin Abdul Wahab, Shaiful Hisham Mat Jali, Mohamad Nizam Kassim, Anazida Zainal, Mohd Aizaini Maarof
Publikováno v:
Smart Innovation, Systems and Technologies ISBN: 9789811500763
Word stemmer (or text stemmer) is used to remove bound morphemes from derived words so that various morphological variants are mapped into common base forms. It is usually used as one of the preprocessing tools in text classification, text mining, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::66ad97fd61634bc04ff9deba5370031b
https://doi.org/10.1007/978-981-15-0077-0_43
https://doi.org/10.1007/978-981-15-0077-0_43
Publikováno v:
Advanced Science Letters. 23:695-698
View references (29) Word stemmer is a preprocessing component that has been widely used in many artificial intelligence applications for reducing derived words to their respective root words. There are many existing Malay word stemmers that have bee
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a8a66af4e8d31cddc7670f5c9a9d80b4
https://doi.org/10.1166/asl.2017.7446
https://doi.org/10.1166/asl.2017.7446
Publikováno v:
2019 International Conference on Cybersecurity (ICoCSec).
Understanding of cybersecurity threat landscape especially information about threat actor is a challenging task as these information are usually hidden and scattered. The online news had became one of the popular and important source of information f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bf5b77b2d329076887e33e5ab9eff1df
https://doi.org/10.1109/icocsec47621.2019.8970979
https://doi.org/10.1109/icocsec47621.2019.8970979
Publikováno v:
2019 International Conference on Cybersecurity (ICoCSec).
Analyzing text especially in Malware domain is quite challenging. Even with Natural Language Processing approach, it limits with the absence of specific Named Entity recognizer to extract related entities of malware from unstructured data like text.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cfa731698da93e6af6f30e83be03c752
https://doi.org/10.1109/icocsec47621.2019.8970801
https://doi.org/10.1109/icocsec47621.2019.8970801