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pro vyhledávání: '"Ahmadi, Mansour"'
Seed scheduling is a prominent factor in determining the yields of hybrid fuzzing. Existing hybrid fuzzers schedule seeds based on fixed heuristics that aim to predict input utilities. However, such heuristics are not generalizable as there exists no
Externí odkaz:
http://arxiv.org/abs/2002.08568
Temporal memory corruptions are commonly exploited software vulnerabilities that can lead to powerful attacks. Despite significant progress made by decades of research on mitigation techniques, existing countermeasures fall short due to either limite
Externí odkaz:
http://arxiv.org/abs/2002.07936
The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0.5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples. Apart from serving in the Kaggle competi
Externí odkaz:
http://arxiv.org/abs/1802.10135
The importance of employing machine learning for malware detection has become explicit to the security community. Several anti-malware vendors have claimed and advertised the application of machine learning in their products in which the inference ph
Externí odkaz:
http://arxiv.org/abs/1802.01185
Modern malware is designed with mutation characteristics, namely polymorphism and metamorphism, which causes an enormous growth in the number of variants of malware samples. Categorization of malware samples on the basis of their behaviors is essenti
Externí odkaz:
http://arxiv.org/abs/1511.04317
Autor:
Ahmadi, Mansour
Increasing competition from traditional and emerging channels has placed new emphasis on rapid innovation and continuous differentiation in every aspect of supply chain, from earliest production stage to the final distribution steps. To bridge the ga
Externí odkaz:
http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16150
Publikováno v:
In Computer Fraud & Security August 2013 2013(8):11-19
Akademický článek
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The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0.5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples. Apart from serving in the Kaggle competi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::066faa41249d4a334a67de49e17830b1
http://arxiv.org/abs/1802.10135
http://arxiv.org/abs/1802.10135
Akademický článek
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