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Record W1599618085

Proceedings of the second ACM workshop on Security and privacy in smartphones and mobile devices

2011· article· en· W1599618085 on OpenAlexaboutno aff
Xuxian Jiang, Amiya Bhattacharya, Partha Dasgupta, William Enck

Bibliographic record

VenueComputer and Communications Security · 2011
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Malware Detection Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPhoneComputer scienceLaptopMobile deviceWorld Wide WebPermissionMobile phoneComputer securityInternet privacyTelecommunicationsPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

It is our great pleasure to welcome you to the Second ACM Workshop on Security and Privacy in Smartphones and Mobile Devices -- SPSM'12, held in association with the 19th ACM Conference on Computer and Communications Security, October 19th, 2012, in Raleigh, NC (USA). The workshop was created last year to organize and foster discussion of security in the emerging area of smartphone and mobile device computing. As organizers of top security venues, we've observed an increasing number of submissions describing novel approaches to solving the challenges of this area. We wanted to provide a dedicated venue to discuss these challenges and promising approaches for future research directions. SPSM'11 was a great success, with an excellent turnout of 80 registered attendees and in-depth discussion. This year, we will continue the 15 minute back-to-back talks followed by 45 minutes of discussion and hope to meet and exceed the high bar that was set. The call for papers attracted 30 submissions from Canada, China, Germany, Greece, India, Iran, Italy, Japan, Lebanon, Nigeria, South Africa, and the United States. The program committee accepted 11 papers that cover a variety of topics, including permission models, user studies, attacks on smartphones, and methods of defense. We are especially pleased to have a keynote speech by Geir Olsen, a Principle Program Manager in the operating systems group on the Windows Phone team, on Windows Phone 8 Security. We hope that these proceedings will serve as a valuable reference for security researchers and developers.

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)0.005
metaresearch head score (Gemma)0.009
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.060
Threshold uncertainty score0.202

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0070.008
Open science0.0020.004
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.0600.023

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 head0.029
GPT teacher head0.271
Teacher spread0.243 · 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

Citations24
Published2011
Admission routes1
Has abstractyes

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