MétaCan
Menu
Back to cohort
Record W2025813221 · doi:10.1002/sec.199

Secure and robust threshold key management (SRKM) scheme for <i>ad hoc</i> networks

2010· article· en· W2025813221 on OpenAlexaff
Khaled Hamouid, Kamel Adi

Bibliographic record

VenueSecurity and Communication Networks · 2010
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversité du Québec en Outaouais
Fundersnot available
KeywordsComputer scienceComputer securityKey managementMobile ad hoc networkAdversaryCertificate authorityPublic-key cryptographyKey (lock)Robustness (evolution)Wireless ad hoc networkVulnerability (computing)Computer networkCertificateCryptographyScheme (mathematics)WirelessEncryptionTelecommunicationsNetwork packetTheoretical computer science

Abstract

fetched live from OpenAlex

Abstract Securing Mobile ad hoc Networks (MANET) is a challenging task, notably due to the lack of an online infrastructure. In particular, key management in MANET is a problem for which many solutions have been proposed in literature. Unfortunately, these solutions are rather limited in terms of security and availability of keys. In this paper, we propose a secure, robust, and fully distributed scheme for public‐key certificate management in MANET. Our scheme, based on threshold cryptography, ensures that the private key of the certificate authority will not be revealed to an adversary, even if the number of compromised shareholders exceeds the threshold of vulnerability, thereby thwarting mobile‐adversary attacks. We describe SRKM in detail and, by using security analysis and simulations, show its effectiveness, robustness and security. Copyright © 2010 John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.223
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations6
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueSecurity and Communication NetworksSame topicMobile Ad Hoc NetworksFrench-language works237,207