Porcedda, MG and Wall, DS orcid.org/0000-0002-6003-1592 (2019) Cascade and Chain Effects in Big Data Cybercrime: Lessons from the TalkTalk hack. In: Proceedings of 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). WACCO 2019: 1st Workshop on Attackers and Cyber-Crime Operations, 2019 IEEE European Symposium on Security and Privacy Workshops, 17-19 Jun 2019, Stockholm, Sweden. IEEE , pp. 443-452. ISBN 978-1-7281-3026-2
Abstract
Big data and cybercrime are creating 'upstream', big data related cyber-dependent crimes such as data breaches. They are essential components in a cybercrime chain which forms a cybercrime ecosystem that cascades 'downstream' to give rise to further crimes, such as fraud, extortion, etc., where the data is subsequently monetized. These downstream crimes have a massive impact upon victims and data subjects. The upstream and downstream crimes are often committed by entirely different offending actors against different victim groups, which complicates and frustrates the reporting, recording, investigative and prosecution processes. Taken together the crime stream's cascade effect creates unprecedented societal challenges that need addressing in the face of the advances of AI and the IoT. This phenomenon is explored here by unpacking the TalkTalk case study to conceptualize how big data and cloud computing are creating cascading effects of disorganized, distributed and escalating data crime. As part of the larger CRITiCal project, the paper also hypothesizes key factors triggering the cascade effect and suggests a methodology to further investigate and understand it.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2019, Maria Grazia Porcedda. Under license to IEEE. This is an author produced version of a paper published in Proceedings of 2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW). Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | cybercrime; big data; big data crime; cloud computing; crime scripts; crime cascade |
Dates: |
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Institution: | The University of Leeds |
Funding Information: | Funder Grant number EPSRC EP/M020576/1 EPSRC EP/P011721/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Jul 2019 10:47 |
Last Modified: | 20 Sep 2019 01:34 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/EuroSPW.2019.00056 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:148986 |