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Record W2130131604 · doi:10.1109/lcn.2008.4664198

Receiver access control and secured handoff in mobile multicast using IGMP-AC

2008· article· en· W2130131604 on OpenAlexafffund
Salekul Islam, J. William Atwood

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsConcordia University
FundersFonds Québécois de la Recherche sur la Nature et les TechnologiesConcordia University
KeywordsComputer networkInternet Group Management ProtocolComputer scienceMulticastIP multicastProtocol Independent MulticastXcastSource-specific multicastPragmatic General Multicast

Abstract

fetched live from OpenAlex

Multicasting has not been widely adopted until now, due to lack of receiver or end user (EU) access control. We have developed the Internet group management protocol with access control (IGMP-AC), an extended version of IGMPv3, which provides EU access control by incorporating the AAA framework into the existing multicast service model. Furthermore, IGMP-AC works as an extensible authentication protocol (EAP) lower layer, and thus, supports a variety of different authentication methods. IP multicast will face new challenges if it has to control mobile EUs accessing valuable data in wireless networks. In the absence of receiver access control the operators of the wireless networks will be reluctant to deploy IP multicast, due to possible wastage of valuable bandwidth and other resources from joining of any unauthorized mobile EU and unwanted extension of the distribution tree. Moreover, multicast suffers from denial of service attack more severely than any other attack because of its amplification of data packets enroute. In this paper, we have broadened the scope of IGMP-AC by demonstrating the usability of IGMP-AC in wireless networks for mobile receiver (or EU) access control. In addition, using EAP re-authentication protocol (ERP), we have developed a procedure for secured and fast handoff of mobile EUs in wireless networks.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.327
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.019
GPT teacher head0.249
Teacher spread0.230 · 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.

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

Citations1
Published2008
Admission routes2
Has abstractyes

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