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Record W2034732438 · doi:10.1109/bsc.2010.5472979

Energy efficiency of symmetric key cryptographic algorithms in wireless sensor networks

2010· article· en· W2034732438 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
TopicSecurity in Wireless Sensor Networks
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsComputer scienceSymmetric-key algorithmBlock cipherKey scheduleCryptographyS-boxAlgorithmWireless sensor networkKey (lock)Stream cipherEfficient energy useEncryptionBlock sizeDifferential cryptanalysisComputer networkPublic-key cryptographyComputer securityEngineering

Abstract

fetched live from OpenAlex

In this paper, we examine the energy efficiency of symmetric key cryptographic algorithms applied in wireless sensor networks (WSNs) and in our study we consider both stream ciphers and block ciphers. We derive the computational energy cost of the ciphers under consideration by comparing the number of CPU cycles required to perform encryption. After evaluating a number of symmetric key ciphers, we compare the energy performance of stream ciphers and block ciphers applied to a noisy channel in a WSN. In conclusion, we recommend using a lightweight block cipher referred to as byte-oriented substitution-permutation network (BSPN), to achieve energy efficiency with a level of security suitable for wireless sensor networks.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.005
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.000
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 head0.007
GPT teacher head0.215
Teacher spread0.208 · 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

Citations51
Published2010
Admission routes1
Has abstractyes

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