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Record W1842898613

Secure group communication

2005· dissertation· en· W1842898613 on OpenAlexaff
Ritesh Mukherjee

Bibliographic record

VenueSpectrum Research Repository (Concordia University) · 2005
Typedissertation
Languageen
FieldComputer Science
TopicCryptography and Data Security
Canadian institutionsConcordia University
Fundersnot available
KeywordsMulticastIP multicastComputer sciencePragmatic General MulticastComputer networkSource-specific multicastXcastSecure multicastProtocol Independent MulticastInter-domainInternet Group Management ProtocolReliable multicastDistributed computing
DOInot available

Abstract

fetched live from OpenAlex

With the advent of digital technologies and widening Internet bandwidth in recent years there has been a marked rise in new multimedia services, including teleconferencing, pay-per-view TV, interactive simulations, software updates and real-time delivery of stock market information. Multicast data distribution has been used in controlled environments to deliver such services. However, the lack of secure, accountable multicast data distribution has prevented its use in general Internet environments. Proposals for multicast security solutions so far are complex and often require trust in intermediate components or are inefficient. A secure multicast protocol suite must provide for data confidentiality, for multicast packet source authentication and for the representation of multicast security policies. In this thesis we present a robust, simple and efficient multicast key management protocol based on proxy encryption, a multicast data source authentication mechanism based on symmetric message authentication codes and a simple multicast policy representation scheme based on XML. The solutions are analyzed and compared to previously published schemes. The results show that the proposed schemes are efficient and scalable when compared to existing 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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.953
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0050.001
Research integrity0.0010.002
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 head0.021
GPT teacher head0.276
Teacher spread0.256 · 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 designTheoretical or conceptual
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
Published2005
Admission routes1
Has abstractyes

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