TorBot Stalker: detecting Tor botnets through intelligent circuit data analysis
- Submitting institution
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University of Portsmouth
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 14316726
- Type
- E - Conference contribution
- DOI
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10.1109/NCA.2018.8548313
- Title of conference / published proceedings
- 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)
- First page
- 1
- Volume
- -
- Issue
- -
- ISSN
- -
- Open access status
- -
- Month of publication
- November
- Year of publication
- 2018
- URL
-
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- Supplementary information
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- Request cross-referral to
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- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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2
- Research group(s)
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C - Cyber Security
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This ground-breaking work developed the first mechanism for detecting, de-anonymizing and destroying Tor botnets, enabling the identification of infected hosts at the Tor network border, in real-time, while preserving the privacy of legitimate users. It received the Best Paper Award at IEEE NCA 2018.
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -