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Record W2159990088 · doi:10.1145/1089803.1089981

On the resiliency of mobile ad hoc networks to MAC layer misbehavior

2005· article· en· W2159990088 on OpenAlexaff
Lei Guang, Chadi Assi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer networkComputer scienceWireless ad hoc networkNode (physics)Vulnerability (computing)Network packetMobile ad hoc networkExploitPacket forwardingComputer securityWirelessTelecommunicationsEngineering

Abstract

fetched live from OpenAlex

This paper describes a new vulnerability for the IEEE 802.11 protocol and studies its impact on degrading the performance of ad hoc networks. A host that exploits this new simple, but practical, vulnerability could cause devastating effects on the proper operation of the network protocols and hence severe performance degradation. Here, a misbehaving node fully cooperates by forwarding packets for other nodes and completely adheres to the proper selection of backoff intervals; however, it maliciously forces the forwarding operation to fail in order to either disrupt the route discovery process or to cause damage to existing flows routed though that node. As a result, the medium around the misbehaving node will be less congested and hence the node will obtain an increased unfair access to the channel. We use network simulations to show that such malicious misbehaviors have devastating effect on demoting the network performance and disrupting the protocol functioning. Hence, necessary extensions for existing detection systems are required to mitigate the effects of these new vulnerabilities.

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 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 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 score0.654
Threshold uncertainty score0.663

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.255
Teacher spread0.242 · 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 teacher head, 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

Citations16
Published2005
Admission routes1
Has abstractyes

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