Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PeerHunter: Detecting Peer-to-Peer Botnets through Community Behavior
  Analysis   Peer-to-peer (P2P) botnets have become one of the major threats in network
security for serving as the infrastructure that responsible for various of
cyber-crimes. Though a few existing work claimed to detect traditional botnets
effectively, the problem of detecting P2P botnets involves more challenges. In
this paper, we present PeerHunter, a community behavior analysis based method,
which is capable of detecting botnets that communicate via a P2P structure.
PeerHunter starts from a P2P hosts detection component. Then, it uses mutual
contacts as the main feature to cluster bots into communities. Finally, it uses
community behavior analysis to detect potential botnet communities and further
identify bot candidates. Through extensive experiments with real and simulated
network traces, PeerHunter can achieve very high detection rate and low false
positives.

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The categories of this paper are: mtrl-th
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
3
The categories of this paper are: physics
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The categories of this paper are: solv-int
18
The categories of this paper are: econ
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
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The categories of this paper are: atom-ph
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The categories of this paper are: nlin
25
The categories of this paper are: patt-sol
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The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
28
The categories of this paper are: alg-geom
14
The categories of this paper are: math-ph