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Record W4200466906 · doi:10.3390/s21248245

Efficient Authentication Protocol and Its Application in Resonant Inductive Coupling Wireless Power Transfer Systems

2021· article· en· W4200466906 on OpenAlexaff
Emmanuel Ahene, Mark Ofori-Oduro, Frimpong Twum, Joojo Walker, Yaw Marfo Missah

Bibliographic record

VenueSensors · 2021
Typearticle
Languageen
FieldEngineering
TopicWireless Power Transfer Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsAuthentication protocolComputer scienceAuthentication (law)Maximum power transfer theoremWireless power transferRobustness (evolution)WirelessProtocol (science)TransmitterWireless securityKey (lock)Cryptographic protocolElectrical engineeringComputer networkCryptographyElectronic engineeringPower (physics)EngineeringComputer securityWireless networkChannel (broadcasting)TelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Chaos theory and its extension into cryptography has generated significant applications in industrial mixing, pulse width modulation and in electric compaction. Likewise, it has merited applications in authentication mechanisms for wireless power transfer systems. Wireless power transfer (WPT) via resonant inductive coupling mechanism enables the charging of electronic devices devoid of cords and wires. In practice, the key to certified charging requires the use of an authentication protocol between a transmitter (charger) and receiver (smartphone/some device). Via the protocol, a safe level and appropriate charging power can be harvested from a charger. Devoid of an efficient authentication protocol, a malicious charger may fry the circuit board of a receiver or cause a permanent damage to the device. In this regard, we first propose a chaos-based key exchange authentication protocol and analyze its robustness in terms of security and computational performance. Secondly, we theoretically demonstrate how the protocol can be applied to WPT systems for the purposes of charger to receiver authentication. Finally, we present insightful research problems that are relevant for future research in this paradigm.

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.

How this classification was reachedexpand

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.402
Threshold uncertainty score0.742

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 communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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