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iCOP: automatically identifying new child abuse media in P2P networks

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

Published

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iCOP : automatically identifying new child abuse media in P2P networks. / Peersman, Claudia; Schulze, Christian; Rashid, Awais; Brennan, Margaret; Fischer, Carl.

2014 IEEE Symposium on Security and Privacy Workshops. IEEE Publishing, 2014. p. 124-131.

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

Harvard

Peersman, C, Schulze, C, Rashid, A, Brennan, M & Fischer, C 2014, iCOP: automatically identifying new child abuse media in P2P networks. in 2014 IEEE Symposium on Security and Privacy Workshops. IEEE Publishing, pp. 124-131.

APA

Peersman, C., Schulze, C., Rashid, A., Brennan, M., & Fischer, C. (2014). iCOP: automatically identifying new child abuse media in P2P networks. In 2014 IEEE Symposium on Security and Privacy Workshops (pp. 124-131). IEEE Publishing.

Vancouver

Peersman C, Schulze C, Rashid A, Brennan M, Fischer C. iCOP: automatically identifying new child abuse media in P2P networks. In 2014 IEEE Symposium on Security and Privacy Workshops. IEEE Publishing. 2014. p. 124-131

Author

Peersman, Claudia ; Schulze, Christian ; Rashid, Awais ; Brennan, Margaret ; Fischer, Carl. / iCOP : automatically identifying new child abuse media in P2P networks. 2014 IEEE Symposium on Security and Privacy Workshops. IEEE Publishing, 2014. pp. 124-131

Bibtex

@inproceedings{b08753b04e554713b1dc4ebd2e9eeac4,
title = "iCOP: automatically identifying new child abuse media in P2P networks",
abstract = "The increasing levels of child sex abuse (CSA) media being shared in peer-to-peer (P2P) networks pose a significant challenge for law enforcement agencies. Although a number of P2P monitoring tools to detect offender activity in such networks exist, they typically rely on hash value databases of known CSA media. Such an approach cannot detect new or previously unknown media being shared. Conversely, identifying such new/previously unknown media is a priority for law enforcement – they can be indicators of recent or on-going child abuse. Furthermore, originators of such media can be hands on abusers and their apprehension can safeguard children from further abuse. The sheer volume of activity on P2P networks, however, makes manual detection virtually infeasible. In this paper, we present a novel approach that combines sophisticated filename and media analysis techniques to automatically flag new/previously unseen CSA media to investigators. The approach has been implemented into the iCOP toolkit. Our evaluation on real case data shows high degrees of accuracy while hands-on trials with law enforcement officers highlight iCOP’s usability and its complementarity to existing investigative workflows.",
author = "Claudia Peersman and Christian Schulze and Awais Rashid and Margaret Brennan and Carl Fischer",
year = "2014",
language = "English",
pages = "124--131",
booktitle = "2014 IEEE Symposium on Security and Privacy Workshops",
publisher = "IEEE Publishing",

}

RIS

TY - GEN

T1 - iCOP

T2 - automatically identifying new child abuse media in P2P networks

AU - Peersman, Claudia

AU - Schulze, Christian

AU - Rashid, Awais

AU - Brennan, Margaret

AU - Fischer, Carl

PY - 2014

Y1 - 2014

N2 - The increasing levels of child sex abuse (CSA) media being shared in peer-to-peer (P2P) networks pose a significant challenge for law enforcement agencies. Although a number of P2P monitoring tools to detect offender activity in such networks exist, they typically rely on hash value databases of known CSA media. Such an approach cannot detect new or previously unknown media being shared. Conversely, identifying such new/previously unknown media is a priority for law enforcement – they can be indicators of recent or on-going child abuse. Furthermore, originators of such media can be hands on abusers and their apprehension can safeguard children from further abuse. The sheer volume of activity on P2P networks, however, makes manual detection virtually infeasible. In this paper, we present a novel approach that combines sophisticated filename and media analysis techniques to automatically flag new/previously unseen CSA media to investigators. The approach has been implemented into the iCOP toolkit. Our evaluation on real case data shows high degrees of accuracy while hands-on trials with law enforcement officers highlight iCOP’s usability and its complementarity to existing investigative workflows.

AB - The increasing levels of child sex abuse (CSA) media being shared in peer-to-peer (P2P) networks pose a significant challenge for law enforcement agencies. Although a number of P2P monitoring tools to detect offender activity in such networks exist, they typically rely on hash value databases of known CSA media. Such an approach cannot detect new or previously unknown media being shared. Conversely, identifying such new/previously unknown media is a priority for law enforcement – they can be indicators of recent or on-going child abuse. Furthermore, originators of such media can be hands on abusers and their apprehension can safeguard children from further abuse. The sheer volume of activity on P2P networks, however, makes manual detection virtually infeasible. In this paper, we present a novel approach that combines sophisticated filename and media analysis techniques to automatically flag new/previously unseen CSA media to investigators. The approach has been implemented into the iCOP toolkit. Our evaluation on real case data shows high degrees of accuracy while hands-on trials with law enforcement officers highlight iCOP’s usability and its complementarity to existing investigative workflows.

M3 - Conference contribution/Paper

SP - 124

EP - 131

BT - 2014 IEEE Symposium on Security and Privacy Workshops

PB - IEEE Publishing

ER -