MétaCan
Menu
Back to cohort
Record W4241666923 · doi:10.32920/ryerson.14652960

Authentication protocols for smart homes

2021· preprint· en· W4241666923 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
Typepreprint
Languageen
FieldComputer Science
TopicAdvanced Authentication Protocols Security
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMutual authenticationPasswordComputer scienceAuthentication (law)Multi-factor authenticationComputer securityScheme (mathematics)Smart cardAuthentication protocolComputer networkChallenge–response authenticationLightweight Extensible Authentication Protocol

Abstract

fetched live from OpenAlex

One of the IoT's greatest opportunity and application still lies ahead in the form of smart home. In this ubiquitous/automated environment, due to the most likely heterogeneity of objects, communication, topology, security protocols, and the computationally limited na- ture of IoT objects, conventional authentication schemes may not comply with IoT security requirements since they are considered impractical, weak, or outdated. This thesis proposes: (1) The design of a two-factor device-to-device (D2D) Mutual Authentication Scheme for Smart Homes using OTP over Infrared Channel (referred to as D2DA-OTP-IC scheme); (2) The design of two proxy-password protected OTP-based schemes for smart homes, namely, the Password Protected Inter-device OTP-based Authentication scheme over Infrared Chan- nel and the Password Protected Inter-device OTP-based Authentication scheme using public key infrastructure; and (3) The design of a RSA-based two-factor user Authentication scheme for Smart Home using Smart Card.

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 categoriesMeta-epidemiology (narrow)
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 score0.388
Threshold uncertainty score1.000

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 science0.0020.002
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 head0.047
GPT teacher head0.359
Teacher spread0.313 · 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