Abstract: A botnet consists of a network of infected computers that can be controlled remotely via a command and control (C&C) server. Typically, a botnet ...
Typically, a botnet requires frequent communication between a C&C server and the infected nodes. Previous approaches to detecting botnets have included various ...
This study attempts to develop a new freeway incident detection algorithm that uses the data of pulse lengths and pulse gaps from the loop detectors as ...
This research conducts autocorrelation analysis of traffic generated by several financial botnets, and it is shown that periodicity in the network traces ...
In this research, we conduct autocorrelation analysis of traffic generated by financial botnets, and we show that periodicity is a highly distinguishing feature ...
Autocorrelation Analysis of Financial Botnet Traffic. Authors: Prathiba Nagarajan, Fabio Di Troia, Thomas H. Austin and Mark Stamp. Abstract: A botnet ...
Financial botnet traffic-based signatures. - ResearchGate
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Based on the results in Table 2, it is clear that periodicity analysis provides a finger- print for each of the four financial botnets considered in this paper.
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The ML-based bot detector first employs supervised ML algorithms for aggregate traffic classification and subsequently Autocorrelation Function (ACF)-based ...
This paper addresses this threat by proposing a method to identify botnets based on distinctive communication patterns between command and control servers and ...
Table 4 lists the detection results using autocorrelation analysis on these HTTP-based botnet traces. The botnets in. B-HTTP-n (n = 1,..., 4) were all detected.
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