Visible to the public Use of Warnings for Instructing Users How to Detect Phishing WebpagesConflict Detection Enabled

TitleUse of Warnings for Instructing Users How to Detect Phishing Webpages
Publication TypeConference Paper
Year of Publication2016
AuthorsAiping Xiong, Robert W. Proctor, Ninghui Li, Weining Yang
Conference Name46th Annual Meeting of the Society for Computers in Psychology
Conference LocationBoston MA
KeywordsA Human Information-Processing Analysis of Online Deception Detection, Human Behavior, NCSU, Oct'16
Abstract

The ineffectiveness of phishing warnings has been attributed to users' poor comprehension of the warning. However, the effectiveness of a phishing warning is typically evaluated at the time when users interact with a suspected phishing webpage, which we call the effect with phishing warning. Nevertheless, users' improved phishing detection when the warning is absent--or the effect of the warning--is the ultimate goal to prevent users from falling for phishing scams. We conducted an online study to evaluate the effect with and of several phishing warning variations, varying the point at which the warning was presented and whether procedural knowledge instruction was included in the warning interface. The current Chrome phishing warning was also included as a control. 360 Amazon Mechanical-Turk workers made submission? 500! word maximum for symposia) decisions about 10 login webpages (8 authentic, 2 fraudulent) with the aid of warning (first phase). After a short distracting task, the workers made the same decisions about 10 different login webpages (8 authentic, 2 fraudulent) without warning. In phase one, the compliance rates with two proposed warning interfaces (98% and 94%) were similar to those of the Chrome warning (98%), regardless of when the warning was presented. In phase two (without warning), performance was better for the condition in which warning with procedural knowledge instruction was presented before the phishing webpage in phase one, suggesting a better of effect than for the other conditions. With the procedural knowledge of how to determine a webpage's legitimacy, users identified phishing webpages more accurately even without the warning being presented.

Citation Keynode-31378