The Emperor's New Security Indicators
Abstract
We evaluate Website authentication measures that are designed to protect users from man-in-the-middle, 'phishing', and other site forgery attacks. We asked 67 bank customers to conduct common online banking tasks. Each time they logged in, we presented increasingly alarming clues that their connection was insecure. First, we removed HTTPS indicators. Next, we removed the participant's site-authentication image--the customer-selected image that many Websites now expect their users to verify before entering their passwords. Finally, we replaced the bank's password-entry page with a warning page. After each clue, we determined whether participants entered their passwords or withheld them. We also investigate how a study's design affects participant behavior: we asked some participants to play a role and others to use their own accounts and passwords. We also presented some participants with security-focused instructions. We confirm prior findings that users ignore HTTPS indicators: no participants withheld their passwords when these indicators were removed. We present the first empirical investigation of site-authentication images, and we find them to be ineffective: even when we removed them, 23 of the 25 (92%) participants who used their own accounts entered their passwords. We also contribute the first empirical evidence that role playing affects participants' security behavior: role-playing participants behaved significantly less securely than those using their own passwords.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Awareness systems built into browser security systems, including security toolbars, domain highlighting for suspected phishing and HTTPS/SSL/TLS connection indicators, were not effective because users would not understand or pay attention to warnings.
“Their results showed that none of these methods were effective because users would not understand or pay attention to warnings.”
From A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks (2016) · cites this paper as Schechter et al. 2007
Cited by
Sorted by citations
Felt, A. P., Ha, E., Egelman, S., Haney, A., Chin, E., & Wagner, D. (2012) · Proceedings of the Eighth Symposium on Usable Privacy and Security · doi:10.1145/2335356.2335360 · Cited by 983 · see citing works
A Taxonomy of Attacks and a Survey of Defence Mechanisms for Semantic Social Engineering Attacks
Heartfield, R., & Loukas, G. (2016) · ACM Computing Surveys · doi:10.1145/2835375 · Cited by 202 · see citing works
Passwords: If We’re So Smart, Why Are We Still Using Them?
Herley, C., van Oorschot, P. C., & Patrick, A. S. (2009) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-03549-4_14 · Cited by 115 · see citing works
Human Cognition Through the Lens of Social Engineering Cyberattacks
Montañez, R., Golob, E., & Xu, S. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.01755 · Cited by 106 · see citing works
Sebastian, G. (2023) · doi:10.2139/ssrn.4454761 · Cited by 56 · see citing works
- Authors
- Schechter, S. E., Dhamija, R., Ozment, A., & Fischer, I.
- Affiliations
- MIT Lincoln Laboratory (US)
- Harvard University (US)
- University of Cambridge (GB)
- Venue
- 2007 IEEE Symposium on Security and Privacy (SP '07)
- Publisher
- IEEE
- Published
- 2007-05
- Pages
- 51-65
- ISSN
- 1081-6011 (ISSN-L)
- OpenAlex
- W2160343382
- Cited by
- 405
- References
- 0
- Citations by year
- 2026: 2 · 2025: 9 · 2024: 6 · 2023: 11 · 2022: 7 · 2021: 13 · 2020: 15 · 2019: 19 · 2018: 22 · 2017: 22 · 2016: 25 · 2015: 27 · 2014: 27 · 2013: 27 · 2012: 34
- FWCI
- 23.98
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- IEEE Symposium on Security and Privacy (S&P) (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › User Authentication and Security Systems
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Physical Sciences › Computer Science › Information Systems › Spam and Phishing Detection
- Keywords
- phishing, man-in-the-middle attacks, online banking security, security warnings, role play, user security behavior, bank customers
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review