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Record W2801242599 · doi:10.1145/3183341

The Password Life Cycle

2018· article· en· W2801242599 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueACM Transactions on Privacy and Security · 2018
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsCarleton University
Fundersnot available
KeywordsPasswordCoping (psychology)Task (project management)PopulationComputer scienceInterviewComputer securityPassword strengthInternet privacyPsychologyEngineeringMedicineOne-time passwordPolitical science

Abstract

fetched live from OpenAlex

Managing passwords is a difficult task for users, who must create, remember, and keep track of large numbers of passwords. In this work, we investigated users’ coping strategies for password management. Through a series of interviews, we identified a “life cycle” of password use and find that users’ central task in coping with their passwords is rationing their effort to best protect their important accounts. We followed up this work by interviewing experts about their password management practices and found that experts rely on the same kinds of coping strategies as non-experts, but that their increased situation awareness of security allows them to better ration their effort into protecting their accounts. Finally, we conducted a survey study to explore how the life cycle model generalizes to the larger population and find that the life cycle and rationing patterns can be seen in the broader population, but that survey respondents were less likely to characterize security management as a challenging task.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.664
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.260
Teacher spread0.241 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it