Abstract:APT malware exploits HTTP to establish communication with a C & C server to hide their malicious activities. Thus, HTTP-based APT malware infection can be discovered by analyzing HTTP traffic. Recent methods have been dependent on the extraction of statistical features from HTTP traffic, which is suitable for machine learning. However, the features they extract from the limited HTTP-based APT malware traffic dataset are too simple to detect APT malware with strong randomness insufficiently. In this paper, … Show more
“…To detect HTTP-based APT malware infection, [111] explored the usage of graph reasoning to build a web request graph using the referrer value in HTTP requests. They discovered that malware-related web access behaviors typically lack referrer values.…”
Section: Table V: Collection Of Academic Defense Methodsmentioning
“…To detect HTTP-based APT malware infection, [111] explored the usage of graph reasoning to build a web request graph using the referrer value in HTTP requests. They discovered that malware-related web access behaviors typically lack referrer values.…”
Section: Table V: Collection Of Academic Defense Methodsmentioning
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