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BOTection: bot detection by building Markov Chain models of bots network behavior

Alternative title:
Conference paper
Abstract:

Botnets continue to be a threat to organizations, thus various machine learning-based botnet detectors have been proposed. However, the capability of such systems in detecting new or unseen botnets is crucial to ensure its robustness against the rapid evolution of botnets. Moreover, it prolongs the effectiveness of the system in detecting bots, avoiding frequent and time-consuming classifier re-training. We present BOTection, a privacy-preserving bot detection system that models the bot netwo...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1145/3320269.3372202

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Kellogg College
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Kellogg College
Role:
Author
Publisher:
Association for Computing Machinery
Host title:
ASIA CCS '20: Proceedings of the 15th ACM Asia Conference on Computer and Communications Security
Pages:
652–664
Publication date:
2020-10-05
Acceptance date:
2019-10-25
Event title:
15th ACM ASIA Conference on Computer and Communications Security (ACM ASIACCS 2020)
Event location:
Taipei, Taiwan
Event website:
https://asiaccs2020.cs.nthu.edu.tw/
Event start date:
2020-10-05
Event end date:
2020-10-09
DOI:
ISBN:
9781450367509
Language:
English
Keywords:
Pubs id:
pubs:1078585
UUID:
uuid:d32c0700-3965-44d2-a697-77177cef97bf
Local pid:
pubs:1078585
Source identifiers:
1078585
Deposit date:
2019-12-23

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