JOURNAL ARTICLE

The Governance of Cybercrime: An Ecological Approach.

  • Published In: Canadian Journal of Criminology & Criminal Justice, 2024, v. 66, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Dupont, Benoît 3 of 3

Abstract

This article focuses on applying an ecological framework to understand and address the complexity of cybercrime, now the most prevalent form of crime in Canada and other developed societies. It conceptualizes cybercrime as an ecosystem comprising three interacting communities—industry, criminal, and security—whose relationships involve competition, predation, and cooperation, producing emergent effects that shape the digital environment. The security community is expanded beyond traditional law enforcement to include diverse public, private, and civil society actors, each wielding regulatory capacities through laws, markets, norms, and technological architecture. The article illustrates this approach with three innovative anti-cybercrime configurations involving Internet Service Providers combating botnets, the NoMoreRansom initiative aiding ransomware victims, and diversion programs redirecting youth hackers toward cybersecurity careers. It argues that interdisciplinary collaboration and systemic, polycentric governance informed by ecological concepts are essential for developing effective policies and interventions in the evolving cybercrime landscape.

Additional Information

  • Source:Canadian Journal of Criminology & Criminal Justice. 2024/05, Vol. 66, Issue 2, p1
  • Document Type:Article
  • Subject Area:Social Sciences and Humanities
  • Publication Date:2024
  • ISSN:1707-7753
  • DOI:10.3138/cjccj-2024-0034
  • Accession Number:180476174
  • Copyright Statement:Copyright of Canadian Journal of Criminology & Criminal Justice is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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