Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/127343
DC Field | Value | Language |
---|---|---|
dc.contributor | 資管評論 | |
dc.creator | Deshpande, Prasad | |
dc.creator | Stamp, Mark | |
dc.date | 2016-03 | |
dc.date.accessioned | 2019-11-20T08:00:32Z | - |
dc.date.available | 2019-11-20T08:00:32Z | - |
dc.date.issued | 2019-11-20T08:00:32Z | - |
dc.identifier.uri | http://nccur.lib.nccu.edu.tw/handle/140.119/127343 | - |
dc.description.abstract | Previous work has shown that well-designed metamorphicmalware can evade many commonly-used malware detection techniques, including signature scanning. In this paper, we consider a previously developed score which is based on function call graph analysis. We test this score on challenging classes of metamorphic malware and we show that the resulting detection rates yield an improvement over other comparable techniques. These results indicate that the function call graph score is among the stronger malware scores developed to date. | |
dc.format.extent | 173 bytes | - |
dc.format.mimetype | text/html | - |
dc.relation | 資管評論 MIS REVIEW : An International Journal, 21(1)&(2), 15-34 | |
dc.subject | Malware ; Function Call Graph ; Metamorphic Software | |
dc.title | Metamorphic Malware Detection Using Function Call Graph Analysis | |
dc.type | article | |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.fulltext | With Fulltext | - |
item.openairetype | article | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
Appears in Collections: | 期刊論文 |
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