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Record W2673338415 · doi:10.1109/ccece.2017.7946657

A context-aware authentication framework for smart homes

2017· article· en· W2673338415 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

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicUser Authentication and Security Systems
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsComputer scienceAuthentication (law)PasswordContext (archaeology)Computer securityInternet of ThingsAccess controlContext awarenessHome automationThe InternetWorld Wide WebInternet privacyHuman–computer interactionTelecommunications

Abstract

fetched live from OpenAlex

There has been a recent rapid increase in the number of Internet of Things (IoT) devices, providing a wide range of services for smart homes such as surveillance cameras, smart lighting, and door locks that can be remotely accessed and controlled. User mobility makes static security mechanisms, such as usernames and passwords, tedious to use. In this paper, we introduce a context-aware authentication framework for smart homes that utilizes contextual information such as the user's location, profile, calendar, request time and access behavior patterns to enable access to home devices. Such contextual information enables our framework to make more informed decisions about whether to accept or deny access requests. The implementation and evaluation demonstrate that the proposed framework provides security in a flexible manner without requiring any additional user intervention.

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: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.976
Threshold uncertainty score0.717

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 studies0.0000.000
Scholarly communication0.0010.000
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 head0.043
GPT teacher head0.318
Teacher spread0.275 · 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

Quick stats

Citations36
Published2017
Admission routes1
Has abstractyes

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