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Influence of Awareness and Training on Cyber Security
Abstract
This article presents the results of a study to determine the impact of a cyber threat education and awareness intervention on changes in user security behavior. Subjects were randomly assigned to one of two introductory lectures about cyber threats due to poor password management. The low-information condition was based on very general background information on passwords and computer security, while the high-information condition included very detailed and specific information on the threats to subjects' use of e-commerce. The pre/post-treatment design was a single, between-subjects factor (information level–low/high), repeated measures study, with password strength at Time 1 and password strength at Time 2 used to measure change in security behavior over a period of two weeks. The study found that at Time 1, participants possessed no significant differences in the strength of their passwords. Two weeks later, the password strength of the participants in the low-information condition was not statistically different than their initial levels, while subjects in the high-information condition demonstrated password ratings 36 percent stronger (t = 17.0, p = .000). It is concluded that when users were educated of the threats to e-commerce and trained about proper security practices, their behavior could be changed to enhance online security for themselves and the firms where they are employed.
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“Primary evaluation is traditionally based on supervised testing in specific case studies [Eminagaoglu et al. 2009; McCrohan et al. 2010].”
From A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks (2016) · cites this paper as McCrohan et al. 2010
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Research works printed but not linked: 20
- Ashford W., 2009, Computerweekly
- Costa P. T., 1989, The NEO PI/FFI manual supplement
- Coviello , A. 2009 . A common call: Architecting a new information security landscape . RSA Conference 2009 , San Francisco , CA . http://www.rsa.com/innovation/docs/ArtC6.pdf(accessed September 18, 2009) .
- 10.1080/10580530701586136 · DOI
- Dinei , F. , C. Herley , and B. Coskun . 2007 . Do strong web passwords accomplish anything? Proceedings of the 2nd USENIX Workshop on Hot Topics in Security , August 1 – 6 , Boston , MA .
- Dutta A., 2002, California Management Review, 45, 67, 10.2307/41166154 · DOI
- el Kettani M. D. E., 2008, ICEGOV2008, 1
- Frank R., 2008, Journal of Accountancy, 206, 37
- Hoonakker , P. , N. Bornoe , and P. Carayon . 2009 . Password authentication from a human factors perspective: Results of a survey among end-users . Proceedings of the Human Factors and Ergonomics Society 53rd Annual Meeting , October 19–23 , San Antonio , Texas . · DOI
- Kirk J., 2010, Computerworld
- McMillan R., 2010, Computerworld
- 10.1145/359168.359172 · DOI
- Pinkas , B. , and T. Sander . 2002 . Securing passwords against dictionary attacks . Proceedings of the 9th ACM Conference on Computer and Communications Security , Washington , DC . http://portal.acm.org/citation.cfm?id=586133(accessed December 14, 2009). · DOI
- 1998, Critical infrastructure protection
- Richardson R., 2008, Computer Security Institute
- 10.2307/258173 · DOI · Paper page
- 1959, Form D
- Xu H., 2007, Workshop on Usable IT Security Management, Symposium on Usable Privacy and Security (SOUPS)
- 10.1057/ejis.2009.9 · DOI
- 10.1080/15332860903467508 · DOI
Cited by
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
Heartfield, R., & Loukas, G. (2016) · ACM Computing Surveys · doi:10.1145/2835375 · Cited by 202
Metadata
- Authors
- McCrohan, K. F., Engel, K., & Harvey, J. W.
- Affiliations
- George Mason University (US)
- Aptima (United States) (US)
- Corresponding author
- McCrohan, Kevin F.
- Venue
- Journal of Internet Commerce
- Publisher
- Informa UK Limited
- Published
- 2010-06-14
- Volume
- 9
- Issue
- 1
- Pages
- 23-41
- ISSN
- 1533-2861 (ISSN-L)
- 1533-287X
- OpenAlex
- W2095019315
- Cited by
- 100
- References
- 0
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 12 · 2023: 9 · 2022: 10 · 2021: 20 · 2020: 8 · 2019: 9 · 2018: 8 · 2017: 3 · 2016: 2 · 2015: 3 · 2014: 2 · 2013: 2 · 2012: 1
- FWCI
- 2.69
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Internet Commerce (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Social Sciences › Sociology and Political Science › Privacy, Security, and Data Protection
- Keywords
- security training, password strength, user security behavior, e-commerce security, password management, internet security
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.