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Record W2048276667 · doi:10.1145/2660267.2660333

The UNIX Process Identity Crisis

2014· article· en· W2048276667 on OpenAlexaff
Mark S. Dittmer, Mahesh Tripunitara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Data Storage Technologies
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsUnixIdentity crisisProcess (computing)Computer scienceIdentity (music)Operating systemPsychologySocial psychologyArt

Abstract

fetched live from OpenAlex

We revisit the setuid family of calls for privilege management that is implemented in several widely-used operating systems. Three of the four commonly used calls in the family are standardized by POSIX. We investigate the current status of setuid, and in the process, challenge some assertions in prior work. We address three sets of questions with regards to the setuid family. (1) Is the POSIX standard indeed broken as prior work suggests? (2) Are implementations POSIX-compliant as claimed? (3) Are the wrapper functions that prior work proposes to circumvent issues with setuid calls correct and usable? Towards (1), we express the standards in a precise syntax that allows us to assess whether they are unambiguous, logically consistent descriptions of well-formed functions. We have discovered that two of the three functions that are standardized fit these criteria, thereby challenging assertions in prior work regarding the quality of the standard. In cases wherein the standard is broken, we give a clear characterization, and suggest that the standard can be fixed easily, but at the cost of backwards-compatibility. Towards (2), we perform a state-space enumeration as in prior work, report on our discoveries, and discuss the implications of non-conformance and differences in implementation. Towards (3), we discuss some issues that we have discovered with prior wrappers. We then propose a new suite of wrapper functions which are designed with a different mindset from prior work, and provide both stronger guarantees with respect to atomicity and a clearer semantics for permanent and temporary changes in process identity. With a fresh approach, our work is a contribution to a well-established approach to privilege management.

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)0.018
metaresearch head score (Gemma)0.034
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 score0.019
Threshold uncertainty score0.097

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.034
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0070.008
Scholarly communication0.0160.030
Open science0.0030.016
Research integrity0.0050.012
Insufficient payload (model declined to judge)0.0190.006

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 head0.012
GPT teacher head0.281
Teacher spread0.269 · 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

Citations9
Published2014
Admission routes1
Has abstractyes

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