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Record W2102724871 · doi:10.1109/tpds.2013.81

Composing Kerberos and Multimedia Internet KEYing (MIKEY) for AuthenticatedTransport of Group Keys

2013· article· en· W2102724871 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

VenueIEEE Transactions on Parallel and Distributed Systems · 2013
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Authentication Protocols Security
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsKerberosComputer scienceGroup keyPublic-key cryptographyComputer securityAuthentication (law)Principal (computer security)Key (lock)CryptographySecurity associationShared secretPublic key infrastructureComputer networkEncryption

Abstract

fetched live from OpenAlex

We motivate and present two designs for the composition of the authentication protocol, Kerberos, and the key transport protocol, Multimedia Internet KEYing (MIKEY) for authenticated transport of cryptographic keys for secure group-communication in enterprise and public-safety settings. A technical challenge, and our main contribution, is the analysis of the security of the composition. Towards this, we design our compositions to have intuitive appeal and thereby less prone to security vulnerabilities. We then employ protocol composition logic (PCL), a state-of-the-art approach for analyzing our composition. For this, we first articulate two properties that are of interest. Both properties are on the group key that is transported; we call them Group Key Confidentiality and Acquisition. Group Key Confidentiality is the property that if a principal possesses the key, then it is an authorized member of the group. Group Key Acquisition is the property that if a principal is a member of the group, then it is able to acquire the group key. In the course of our rigorous analysis, we discovered a flaw in our first design, which we point out, and which lead us to our second design. We have implemented both designs starting with the publicly available reference implementation of Kerberos, and an open-source implementation of MIKEY. Our implementations are available as open-source. We discuss our experience from the implementation, and present empirical results.

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 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 score0.967
Threshold uncertainty score0.740

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