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Security Measures for Mobile Ad-Hoc Networks (MANETs)

2008· book-chapter· en· W2481426112 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

VenueIGI Global eBooks · 2008
Typebook-chapter
Languageen
FieldComputer Science
TopicAdvanced Authentication Protocols Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsMobile ad hoc networkComputer scienceComputer networkWireless ad hoc networkComputer securityVehicular ad hoc networkKey (lock)Key managementPopularityQuality of serviceVariety (cybernetics)TelecommunicationsWirelessEncryption

Abstract

fetched live from OpenAlex

Mobile ad hoc networks (MANETs) have gained popularity in the past decade with the creation of a variety of ad hoc protocols that specifically offer quality of service (QoS) for various multimedia traffic between mobile stations (MSs) and base stations (BSs). The lack of proper end-to-end security coverage, on the other hand, is a challenging issue as the nature of such networks with no specific infrastructure is prone to relatively more attacks, in a variety of forms. The focus of this chapter is to discuss a number of attack scenarios and their remedies in MANETs including the introduction of two entities; ad hoc key distribution center (AKDC) and decentralize key generation and distribution (DKGD), which serve as key management schemes.

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)0.000
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: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.424
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.000
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 head0.020
GPT teacher head0.271
Teacher spread0.251 · 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