Is Domain Highlighting Actually Helpful in Identifying Phishing Web Pages?

Xiong, Aiping; Proctor, Robert W.; Yang, Weining; Li, Ninghui

doi:10.1177/0018720816684064

Cited by 27 publications

(35 citation statements)

References 35 publications

(44 reference statements)

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“…So, domain name highlighting cannot be used as a single method for detecting phishing webpages. A similar study has been done on a larger scale (320 participants), which resulted in a similar conclusion [213].…”

Section: Selected User Study Literaturesupporting

confidence: 59%

“…[266] 4 [225], [229], [247], [265] 2 [233], [252] 1 [219] No 6 [10], [230], [238], [249], [250], [258] 3 [242], [260], [263] Webpage Yes 5 [204], [239], [245], [253], [261] No 4 [203], [212], [236], [264] 3 [211], [213], [216] 3 [61], [217], [ [232] in [211] and [214] used Functional Magnetic Resonance Imaging (fMRI) and Electroencephalogram (EEG) to measure brain's electrical activity and an eye-tracker to have a better understanding of users' decision-making process. They used both existing phishing websites (by downloading and hosting them on their own network) and manually created ones.…”

Section: Selected User Study Literaturementioning

confidence: 99%

See 1 more Smart Citation

SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective

Das

Baki

Aassal

et al. 2020

IEEE Commun. Surv. Tutorials

101

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Phishing and spear phishing are typical examples of masquerade attacks since trust is built up through impersonation for the attack to succeed. Given the prevalence of these attacks, considerable research has been conducted on these problems along multiple dimensions. We reexamine the existing research on phishing and spear phishing from the perspective of the unique needs of the security domain, which we call security challenges: real-time detection, active attacker, dataset quality and baserate fallacy. We explain these challenges and then survey the existing phishing/spear phishing solutions in their light. This viewpoint consolidates the literature and illuminates several opportunities for improving existing solutions. We organize the existing literature based on detection techniques for different attack vectors (e.g., URLs, websites, emails) along with studies on user awareness. For detection techniques we examine properties of the dataset, feature extraction, detection algorithms used, and performance evaluation metrics. This work can help guide the development of more effective defenses for phishing, spear phishing and email masquerade attacks of the future, as well as provide a framework for a thorough evaluation and comparison.

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Section: Selected User Study Literaturesupporting

confidence: 59%

Section: Selected User Study Literaturementioning

confidence: 99%

SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective

Das

Baki

Aassal

et al. 2020

IEEE Commun. Surv. Tutorials

101

View full text Add to dashboard Cite

show abstract

“…Human education papers commonly teach users how to parse out the domain as a way of enabling them to compare the domain to the one they expect to be visiting [12,36]- [38]. However, people struggle to retain these skills [36].…”

Section: A Url Lexical Featuresmentioning

confidence: 99%

“…Human-facing methods in our dataset did not consider the URL length as a feature; nevertheless, participants in [38] assumed the longer the URL the less secure it was. Alsharnouby et al [26] also found that people without training tend to classify URLs based on their perceived simplicity.…”

Section: A Url Lexical Featuresmentioning

confidence: 99%

A Review of Human- and Computer-Facing URL Phishing Features

Althobaiti

Rummani

Vaniea

2019

2019 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)

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When detecting phishing websites, both humans and computers rely on aspects of the website (features) to aid in their decision making. In this work, we conduct a review of URL-based phishing features that appear in publications targeting humanfacing and automated anti-phishing approaches. We focus on both humans and computers to obtain a more comprehensive feature list and create a cross-community foundation for future research. We reviewed 94 papers and categorise their features into: lexical, host, rank, redirection, certificate, search engine, and black/white lists. We find that research on automation has used all feature categories but several, such as host-based features (e.g. DNS), are minimally explored in human-facing anti-phishing research.

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“…For example, incorporating fear appeals into a password strength meter has been shown to be effective in pushing users towards creating stronger passwords in a field experiment setting (Vance et al 2013). Also, interactively highlighting potentially risky domain names has been shown to be effective in preventing users from visiting phishing websites (Xiong et al 2017). Evidently, this form of assistance is incredibly useful in shaping user behavior and thus has been a focus for both academic researchers and practitioners in the area of information security in recent years.…”

Section: Active Interventionmentioning

confidence: 99%

Enhancing security behaviour by supporting the user

Furnell

Khern-am-nuai

Esmael

et al. 2018

Computers & Security

Self Cite

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Although the role of users in maintaining security is regularly emphasized, this is often not matched by an accompanying level of support. Indeed, users are frequently given insufficient guidance to enable effective security choices and decisions, which can lead to perceived bad behaviour as a consequence. This paper discusses the forms of support that are possible, and seeks to investigate the effect of doing so in practice. Specifically, it presents findings from two experimental studies that investigate how variations in password meter usage and feedback can positively affect the resulting password choices. The first experiment examines the difference between passwords selected by unguided users versus those receiving guidance and alternative forms of feedback (ranging from a traditional password meter through to an emoji-based approach). The findings reveal a 30% drop in weak password choices between unguided and guided usage, with the varying meters then delivering up to 10% further improvement. The second experiment then considers variations in the form of feedback message that users may receive in addition to a meter-based rating. It is shown that by providing richer information (e.g. based upon the time required to crack a password, its relative ranking against other choices, or the probability of it being cracked), users are more motivated towards making strong choices and changing initially weak ones. While the specifics of the experimental findings were focused upon passwords, the discussion also considers the benefits that may be gained by applying the same principles of nudging and guidance to other areas of security in which users are often found to have weak behaviours.

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Is Domain Highlighting Actually Helpful in Identifying Phishing Web Pages?

Abstract: Potential applications include development of phishing prevention training incorporating domain highlighting with other methods to help users identify phishing Web pages.

Cited by 27 publications

References 35 publications

SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective

SoK: A Comprehensive Reexamination of Phishing Research From the Security Perspective

A Review of Human- and Computer-Facing URL Phishing Features

Enhancing security behaviour by supporting the user

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