2013 | OriginalPaper | Chapter
NetGator: Malware Detection Using Program Interactive Challenges
Authors : Brian Schulte, Haris Andrianakis, Kun Sun, Angelos Stavrou
Published in: Detection of Intrusions and Malware, and Vulnerability Assessment
Publisher: Springer Berlin Heidelberg
Activate our intelligent search to find suitable subject content or patents.
Select sections of text to find matching patents with Artificial Intelligence. powered by
Select sections of text to find additional relevant content using AI-assisted search. powered by
Internet-borne threats have evolved from easy to detect denial of service attacks to zero-day exploits used for targeted exfiltration of data. Current intrusion detection systems cannot always keep-up with zero-day attacks and it is often the case that valuable data have already been communicated to an external party over an encrypted or plain text connection before the intrusion is detected.
In this paper, we present a scalable approach called
Network Interrogator (NetGator)
to detect network-based malware that attempts to exfiltrate data over open ports and protocols. NetGator operates as a transparent proxy using protocol analysis to first identify the declared client application using known network flow signatures.Then we craft packets that “challenge” the application by exercising functionality present in legitimate applications but too complex or intricate to be present in malware. When the application is unable to correctly solve and respond to the challenge, NetGator flags the flow as potential malware. Our approach is seamless and requires no interaction from the user and no changes on the commodity application software. NetGator introduces a minimal traffic latency (0.35 seconds on average) to normal network communication while it can expose a wide-range of existing malware threats.