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Protecting ASP.NET Web Services

2008· book-chapter· en· W2504503681 on OpenAlexaff
Konstantin Beznosov

Bibliographic record

VenueIGI Global eBooks · 2008
Typebook-chapter
Languageen
FieldComputer Science
TopicService-Oriented Architecture and Web Services
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWeb application securityComputer scienceWeb serviceWorld Wide WebComputer securityService-oriented architectureASP.NETWeb development

Abstract

fetched live from OpenAlex

This chapter reports on our experience of designing and implementing an architecture for protecting enterprise-grade Web service applications hosted by ASP.NET. Security mechanisms of Microsoft ASP.NET container—a popular hosting environment for Web services—have limited scalability, flexibility, and extensibility. They are therefore inade-quate for hosting enterprise-scale applications that need to be protected according to diverse and/or complex application-specific security policies. To overcome the limitations of ASP.NET security, we developed a flexible and extensible protection architecture. Deployed in a real-world security solution at a financial organization, the architecture enables integra-tion of ASP.NET into the organizational security infrastructure with reduced effort on the part of Web Service developers. Throughout this report, we discuss our design decisions, suggest best practices for constructing flexible and extensible authentication and authoriza-tion logic for Web Services, and share lessons learned.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.004
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.006

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 head0.011
GPT teacher head0.217
Teacher spread0.206 · 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
GenreOther

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

Citations0
Published2008
Admission routes1
Has abstractyes

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