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Why phishing works

Published: 22 April 2006 Publication History

Abstract

To build systems shielding users from fraudulent (or phishing) websites, designers need to know which attack strategies work and why. This paper provides the first empirical evidence about which malicious strategies are successful at deceiving general users. We first analyzed a large set of captured phishing attacks and developed a set of hypotheses about why these strategies might work. We then assessed these hypotheses with a usability study in which 22 participants were shown 20 web sites and asked to determine which ones were fraudulent. We found that 23% of the participants did not look at browser-based cues such as the address bar, status bar and the security indicators, leading to incorrect choices 40% of the time. We also found that some visual deception attacks can fool even the most sophisticated users. These results illustrate that standard security indicators are not effective for a substantial fraction of users, and suggest that alternative approaches are needed.

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Cited By

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  • (2024)Development of a Phishing Detection System Using Support Vector MachineInternational Journal of Innovative Science and Research Technology (IJISRT)10.38124/ijisrt/IJISRT24MAY353(247-257)Online publication date: 17-May-2024
  • (2024)Developing a Multi-Layered Defence System to Safeguard Data against Phishing AttacksInternational Journal of Innovative Science and Research Technology (IJISRT)10.38124/ijisrt/IJISRT24FEB1107(2022-2033)Online publication date: 5-Apr-2024
  • (2024)AntiPhishStack: LSTM-Based Stacked Generalization Model for Optimized Phishing URL DetectionSymmetry10.3390/sym1602024816:2(248)Online publication date: 17-Feb-2024
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Published In

cover image ACM Conferences
CHI '06: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
April 2006
1353 pages
ISBN:1595933727
DOI:10.1145/1124772
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 April 2006

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Author Tags

  1. phishing
  2. phishing user study
  3. security usability
  4. why phishing works

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CHI06
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CHI06: CHI 2006 Conference on Human Factors in Computing Systems
April 22 - 27, 2006
Québec, Montréal, Canada

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Overall Acceptance Rate 6,199 of 26,314 submissions, 24%

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Cited By

View all
  • (2024)Development of a Phishing Detection System Using Support Vector MachineInternational Journal of Innovative Science and Research Technology (IJISRT)10.38124/ijisrt/IJISRT24MAY353(247-257)Online publication date: 17-May-2024
  • (2024)Developing a Multi-Layered Defence System to Safeguard Data against Phishing AttacksInternational Journal of Innovative Science and Research Technology (IJISRT)10.38124/ijisrt/IJISRT24FEB1107(2022-2033)Online publication date: 5-Apr-2024
  • (2024)AntiPhishStack: LSTM-Based Stacked Generalization Model for Optimized Phishing URL DetectionSymmetry10.3390/sym1602024816:2(248)Online publication date: 17-Feb-2024
  • (2024)Prompt Engineering or Fine-Tuning? A Case Study on Phishing Detection with Large Language ModelsMachine Learning and Knowledge Extraction10.3390/make60100186:1(367-384)Online publication date: 6-Feb-2024
  • (2024)'Protect and Fight Back': A Case Study on User Motivations to Report Phishing EmailsProceedings of the 2024 European Symposium on Usable Security10.1145/3688459.3688473(30-43)Online publication date: 30-Sep-2024
  • (2024)UWB-Auth: A UWB-based Two Factor Authentication PlatformProceedings of the 17th ACM Conference on Security and Privacy in Wireless and Mobile Networks10.1145/3643833.3656113(185-195)Online publication date: 27-May-2024
  • (2024)Cognition in Social Engineering Empirical Research: A Systematic Literature ReviewACM Transactions on Computer-Human Interaction10.1145/363514931:2(1-55)Online publication date: 29-Jan-2024
  • (2024)Deep Dive into Client-Side Anti-Phishing: A Longitudinal Study Bridging Academia and IndustryProceedings of the 19th ACM Asia Conference on Computer and Communications Security10.1145/3634737.3657027(638-653)Online publication date: 1-Jul-2024
  • (2024)Two-Factor Authentication for Keyless Entry System via Finger-Induced VibrationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.336833123:10(9708-9720)Online publication date: Oct-2024
  • (2024)ZETAR: Modeling and Computational Design of Strategic and Adaptive Compliance PoliciesIEEE Transactions on Computational Social Systems10.1109/TCSS.2023.332353911:3(4001-4015)Online publication date: Jun-2024
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