MétaCan
Menu
Back to cohort
Record W2086883455 · doi:10.1002/sec.122

PCM: a privacy‐preserving detection mechanism in mobile<i>ad hoc</i>networks

2009· article· en· W2086883455 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSecurity and Communication Networks · 2009
Typearticle
Languageen
FieldComputer Science
TopicPrivacy-Preserving Technologies in Data
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsComputer scienceAnonymityComputer securityWitnessRevocationMobile ad hoc networkWireless ad hoc networkInternet privacyVehicular ad hoc networkComputer networkOverhead (engineering)Network packetTelecommunicationsWireless

Abstract

fetched live from OpenAlex

Abstract Although extensive research work has been undertaken to secure mobile ad hoc networks, till recently, researchers began to pay attention to the anonymity issue, and this issue was investigated mainly in terms of secure routing and data forwarding. We indicate that, in mobile ad hoc networks, there is an increasing interest in providing anonymity for the witnesses, i.e., those users who share their knowledge in detecting either malicious or selfish users. On the other hand, it is also a challenging problem to prevent the misuse of anonymous sources. In this paper, we propose the PlainClothesMan (PCM) protocol to provide anonymity for the witness who helps identify malicious or selfish users. Once there are more than a certain number of claims from distinct users against the same user, she is identified as a malicious or selfish user. Moreover, in PCM, the misuse of the witness anonymity is prevented in such a way that any malicious user who broadcasts multiple invalid claims against the same user for the same reason can be identified. Two exemplary scenarios are designed and simulated to model the necessities of witness anonymity in mobile ad hoc networks. Simulation results show that witness anonymity is very important for ensuring proper and efficient executions of fundamental functionalities of mobile ad hoc networks, e.g., certificate revocation and fairness, and PCM is both effective and efficient in providing such a type of anonymity. Copyright © 2009 John Wiley &amp; 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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science
Consensus categoriesOpen science
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.963
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0170.031
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 head0.014
GPT teacher head0.250
Teacher spread0.236 · 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