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Record W2098021671 · doi:10.1109/pimrc.2008.4699796

Reducing re-authentication delays during UMTS-WLAN vertical handovers

2008· article· en· W2098021671 on OpenAlexaff
Ali Al Shidhani, Victor C. M. Leung

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsComputer networkComputer scienceUMTS frequency bandsHandoverAuthentication protocolAuthentication (law)Authentication serverMutual authenticationQuality of serviceComputer security

Abstract

fetched live from OpenAlex

Interworking universal mobile telecommunication systems (UMTS) and IEEE 802.11 wireless local area networks (WLANs) introduces new challenges in the design of secured and fast vertical handover (VH) protocols. VH operations must not compromise the security of the network. In addition, VH delays must be minimized to maintain the quality of service of the applications running on the user equipment (UE). Re-authentication is normally required during UMTS-WLAN VH. Existing re-authentication protocols invoked in UMTS-WLAN VH are either inadequately secure or introduces unacceptable delays. This paper proposes couple of re-authentication protocols that reduce re-authentication delays during UMTS-WLAN VHs compared to existing protocols by substantially reducing message signaling. Additionally, they achieve secured key management and mutual authentication between the UE and authentication servers in the 3G home network.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.204
Teacher spread0.191 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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

Citations11
Published2008
Admission routes1
Has abstractyes

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