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Scamming the scammers: towards automatic detection of persuasion in advance fee frauds

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Scamming the scammers: towards automatic detection of persuasion in advance fee frauds. / Edwards, Matthew John; Peersman, Claudia; Rashid, Awais.
Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW). New York: ACM, 2017. p. 1291-1299.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Harvard

Edwards, MJ, Peersman, C & Rashid, A 2017, Scamming the scammers: towards automatic detection of persuasion in advance fee frauds. in Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW). ACM, New York, pp. 1291-1299. https://doi.org/10.1145/3041021.3053889

APA

Edwards, M. J., Peersman, C., & Rashid, A. (2017). Scamming the scammers: towards automatic detection of persuasion in advance fee frauds. In Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW) (pp. 1291-1299). ACM. https://doi.org/10.1145/3041021.3053889

Vancouver

Edwards MJ, Peersman C, Rashid A. Scamming the scammers: towards automatic detection of persuasion in advance fee frauds. In Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW). New York: ACM. 2017. p. 1291-1299 doi: 10.1145/3041021.3053889

Author

Edwards, Matthew John ; Peersman, Claudia ; Rashid, Awais. / Scamming the scammers : towards automatic detection of persuasion in advance fee frauds. Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW). New York : ACM, 2017. pp. 1291-1299

Bibtex

@inproceedings{865a1d6c35ae42aa8f813d6bc1894c6e,
title = "Scamming the scammers: towards automatic detection of persuasion in advance fee frauds",
abstract = "Advance fee fraud is a significant component of online criminal activity. Fraudsters can often make off with significant sums, and victims will usually find themselves plagued by follow-up scams. Previous studies of how fraudsters persuade their victims have been limited to the initial solicitation emails sent to a broad population of email users. In this paper, we use the lens of scam-baiting – a vigilante activity whereby members of the public intentionally waste the time of fraudsters – to move beyond this first contact and examine the persuasive tactics employed by a fraudster once their victim has responded to a scam. We find linguistic patterns in scammer and baiter communications that suggest that the mode of persuasion used by scammers shifts over a conversation, and describe a corresponding stage model of scammer persuasion strategy. We design and evaluate a number of classifiers for identifying scam-baiting conversations amidst regular email, and for separating scammer from baiter messages based on their textual content, achieving high classification accuracy for both tasks. This forms a crucial basis for automated intervention, with a tool for identifying victims and a model for understanding how they are currently being exploited.",
author = "Edwards, {Matthew John} and Claudia Peersman and Awais Rashid",
year = "2017",
month = apr,
day = "3",
doi = "10.1145/3041021.3053889",
language = "English",
isbn = "9781450349147",
pages = "1291--1299",
booktitle = "Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW)",
publisher = "ACM",

}

RIS

TY - GEN

T1 - Scamming the scammers

T2 - towards automatic detection of persuasion in advance fee frauds

AU - Edwards, Matthew John

AU - Peersman, Claudia

AU - Rashid, Awais

PY - 2017/4/3

Y1 - 2017/4/3

N2 - Advance fee fraud is a significant component of online criminal activity. Fraudsters can often make off with significant sums, and victims will usually find themselves plagued by follow-up scams. Previous studies of how fraudsters persuade their victims have been limited to the initial solicitation emails sent to a broad population of email users. In this paper, we use the lens of scam-baiting – a vigilante activity whereby members of the public intentionally waste the time of fraudsters – to move beyond this first contact and examine the persuasive tactics employed by a fraudster once their victim has responded to a scam. We find linguistic patterns in scammer and baiter communications that suggest that the mode of persuasion used by scammers shifts over a conversation, and describe a corresponding stage model of scammer persuasion strategy. We design and evaluate a number of classifiers for identifying scam-baiting conversations amidst regular email, and for separating scammer from baiter messages based on their textual content, achieving high classification accuracy for both tasks. This forms a crucial basis for automated intervention, with a tool for identifying victims and a model for understanding how they are currently being exploited.

AB - Advance fee fraud is a significant component of online criminal activity. Fraudsters can often make off with significant sums, and victims will usually find themselves plagued by follow-up scams. Previous studies of how fraudsters persuade their victims have been limited to the initial solicitation emails sent to a broad population of email users. In this paper, we use the lens of scam-baiting – a vigilante activity whereby members of the public intentionally waste the time of fraudsters – to move beyond this first contact and examine the persuasive tactics employed by a fraudster once their victim has responded to a scam. We find linguistic patterns in scammer and baiter communications that suggest that the mode of persuasion used by scammers shifts over a conversation, and describe a corresponding stage model of scammer persuasion strategy. We design and evaluate a number of classifiers for identifying scam-baiting conversations amidst regular email, and for separating scammer from baiter messages based on their textual content, achieving high classification accuracy for both tasks. This forms a crucial basis for automated intervention, with a tool for identifying victims and a model for understanding how they are currently being exploited.

U2 - 10.1145/3041021.3053889

DO - 10.1145/3041021.3053889

M3 - Conference contribution/Paper

SN - 9781450349147

SP - 1291

EP - 1299

BT - Second International Workshop on Computational Methods for CyberSafety (CyberSafety 2017) co-located with International Conference on World Wide Web (WWW)

PB - ACM

CY - New York

ER -