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Record W3081218576 · doi:10.1109/jsyst.2020.3015424

A Secure and Lightweight Protocol for Message Authentication in Wireless Sensor Networks

2020· article· en· W3081218576 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

VenueIEEE Systems Journal · 2020
Typearticle
Languageen
FieldComputer Science
TopicSecurity in Wireless Sensor Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkAuthentication (law)Message authentication codeWireless sensor networkOverhead (engineering)Authentication protocolKey distribution in wireless sensor networksNode (physics)WirelessWireless networkComputer securityCryptographyEngineering

Abstract

fetched live from OpenAlex

Securing messages and protecting them from tampering during transmission in wireless sensor networks is a challenging task. Using message authentication schemes provides security and authentication, but with a high computational and communication cost. Sensors are highly constrained in terms of computational capabilities and power consumption. Therefore, computation is divided into two phases: online (at the sensor) and offline (at a more powerful central node). Moreover, public keys are generated based on the identities to reduce communication overhead. In this article, we propose a message authentication scheme based on identity that uses online/offline signature. We prove that the scheme provides and protects the integrity of messages during the transmission of data over an insecure network. Our scheme is existential unforgeable against chosen message attack.

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)0.001
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: none
Teacher disagreement score0.959
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.030
GPT teacher head0.279
Teacher spread0.249 · 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