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Record W2096927040 · doi:10.1155/2010/258935

COSR: A Reputation-Based Secure Route Protocol in MANET

2010· article· en· W2096927040 on OpenAlexaff
Fei Wang, Furong Wang, Benxiong Huang, Laurence T. Yang

Bibliographic record

VenueEURASIP Journal on Wireless Communications and Networking · 2010
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsSt. Francis Xavier University
FundersProgram for New Century Excellent Talents in University
KeywordsComputer scienceComputer networkMobile ad hoc networkReputationNode (physics)Protocol (science)Computer securityWireless ad hoc networkRouting protocolDistributed computingRouting (electronic design automation)TelecommunicationsWireless

Abstract

fetched live from OpenAlex

Now, the route protocols defined in the Mobile Ad Hoc Network (MANET) are constructed in a common assumption which all nodes contained in such networks are trustworthy and cooperative. Once malicious or selfish nodes exist, all route paths built by these protocols must be broken immediately. According to the secure problems within MANET, this paper proposes Cooperative On-demand Secure Route (COSR), a novel secure source route protocol, against malicious and selfish behaviors. COSR measures node reputation (NR) and route reputation (RR) by contribution, Capability of Forwarding (CoF) and recommendation upon Dynamic Source Route (DSR) and uses RR to balance load to avoid hotpoint. Furthermore, COSR defines path collection algorithm by NR to enhance efficiency of protocol. At last, we verify COSR through GloMoSim. Results show that COSR is secure and stable.

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)0.002
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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

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 head0.022
GPT teacher head0.295
Teacher spread0.273 · 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

Citations26
Published2010
Admission routes1
Has abstractyes

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Same venueEURASIP Journal on Wireless Communications and NetworkingSame topicMobile Ad Hoc NetworksFrench-language works237,207