Cue Utilization, Phishing Feature and Phishing Email Detection Piers Bayl-Smith [0000-0001-8014-0633] , Daniel Sturman [0000-0002-5025-598X] , and Mark Wiggins [0000-0002-6422-9475] Macquarie University, New South Wales, Australia Abstract. Cognitive processes are broadly considered to be of vital importance to understanding phishing email feature detection or misidentification. This re- search extends the current literature by introducing the concept of cue utilization as a unique predictor of phishing feature detection. First year psychology students (n=127) undertook three tasks measuring cue utilization, phishing feature detec- tion and phishing email detection. A multiple linear regression model provided evidence that those in a higher cue utilization typology (n=55) performed better at identifying phishing features than those in a lower cue utilization typology (n=72). Furthermore, as predicted by the Elaboration Likelihood Model (ELM) and Heuristic-Systematic Model (HSM), those who deliberated longer per email demonstrated an increased ability to correctly identify phishing features. How- ever, these results did not translate into improved performance in the phishing email detection task. Possible explanations for these results are discussed, includ- ing possible limitations and areas of future research. Keywords. Phishing; Cue utilization; Feature identification; Elaboration Likeli- hood Model; Heuristic-Systematic Model 1 Introduction 1.1 Study Aims Despite significant investment in cyber security solutions, employees remain the most significant risk to maintaining a protected information environment. Specifically, phishing emails are a major attack vector through which an organization’s information security can be compromised. Recent research has suggested that for businesses, 74% of all cyber threats originate via email sources [1], whereas in Australia, phishing was the top registered scam category reported to the Australian Competition and Consumer Commission [2]. Costs to businesses and individuals have steadily been on the rise at a global level, occasioning in business disruption, information and intellectual property loss, and revenue loss, with damages reported in the hundreds of millions of dollars [2, 3]. Given the importance of human factors and phishing, this study investigates what cognitive factors may influence phishing detection. In particular, whether