A comparison of features in a crowdsourced phishing warning system. (11th March 2021)
- Record Type:
- Journal Article
- Title:
- A comparison of features in a crowdsourced phishing warning system. (11th March 2021)
- Main Title:
- A comparison of features in a crowdsourced phishing warning system
- Authors:
- Nguyen, Christopher
Jensen, Matthew L.
Durcikova, Alexandra
Wright, Ryan T. - Abstract:
- Abstract: Initial research on using crowdsourcing as a collaborative method for helping individuals identify phishing messages has shown promising results. However, the vast majority of crowdsourcing research has focussed on crowdsourced system components broadly and understanding individuals' motivation in contributing to crowdsourced systems. Little research has examined the features of crowdsourced systems that influence whether individuals utilise this information, particularly in the context of warnings for phishing emails. Thus, the present study examined four features related to warnings derived from a mock crowdsourced anti‐phishing warning system that 438 participants were provided to aid in their evaluation of a series of email messages: the number of times an email message was reported as being potentially suspicious, the source of the reports, the accuracy rate of the warnings (based on reports) and the disclosure of the accuracy rate. The results showed that crowdsourcing features work together to encourage warning acceptance and reduce anxiety. Accuracy rate demonstrated the most prominent effects on outcomes related to judgement accuracy, adherence to warning recommendations and anxiety with system use. The results are discussed regarding implications for organisations considering the design and implementation of crowdsourced phishing warning systems that facilitate accurate recommendations.
- Is Part Of:
- Information systems journal. Volume 31:Number 3(2021)
- Journal:
- Information systems journal
- Issue:
- Volume 31:Number 3(2021)
- Issue Display:
- Volume 31, Issue 3 (2021)
- Year:
- 2021
- Volume:
- 31
- Issue:
- 3
- Issue Sort Value:
- 2021-0031-0003-0000
- Page Start:
- 473
- Page End:
- 513
- Publication Date:
- 2021-03-11
- Subjects:
- accuracy -- crowdsourcing -- human‐automation interaction -- phishing -- report source -- warning
Information technology -- Periodicals
Management information systems -- Periodicals
303.4833 - Journal URLs:
- http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code=isj ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2575 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/isj.12318 ↗
- Languages:
- English
- ISSNs:
- 1350-1917
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.368300
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 16354.xml