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Record W4289387959 · doi:10.1145/3266444

Proceedings of the 2018 Workshop on Attacks and Solutions in Hardware Security

2018· paratext· en· W4289387959 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.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

Venuenot available
Typeparatext
Languageen
FieldComputer Science
TopicPhysical Unclonable Functions (PUFs) and Hardware Security
Canadian institutionsnot available
Fundersnot available
KeywordsHardware security moduleComputer scienceDisk formattingComputer securityOrder (exchange)CryptographyBusinessOperating system

Abstract

fetched live from OpenAlex

It is our great pleasure to welcome you to the Second Workshop on Attacks and Solutions in Hardware Security 2018 (ASHES 2018), a post-conference satellite workshop of the ACM Conference on Computer and Communications Security 2018 (CCS 2018) in Toronto, Canada! ASHES deals with all aspects of hardware security, and welcomes any contributions to this area. Besides being a forum for mainstream hardware security research, its mission is to specifically foster new concepts, solutions, and methodological approaches, and to promote new application scenarios. This includes, for example, new attack vectors on secure hardware, the merger of nanotechnology and hardware security, novel designs and materials, lightweight security hardware, and physical unclonable functions (PUFs) on the methodological side, as well as the internet of things, automotive security, smart homes, supply chain security, pervasive and wearable computing on the applications side. ASHES thereby aims at giving researchers and practitioners a unique opportunity to share their perspectives with others on various emerging aspects of hardware security research. In order to account for hardware security as a rapidly developing discipline, ASHES routinely offers four categories of submission: Full papers; Short papers;Systematization of Knowledge (SoK) papers, which structure or survey a certain subarea within hardware security; Wild and Crazy (WaC) papers, whose aim is to distribute a promising and potentially seminal research idea at an early stage to the community. Our call for papers this year attracted 30 submissions overall, of which 27 were conforming to submission and formatting requirements. This marks an increase of 50 percent compared to last year, where ASHES 2017 had received 20 submissions. Two submissions fell into the wild-andcrazy paper category; one into the systematization of knowledge category; the rest were regular full and short papers. Geographically, the different co-authors of submissions this year were associated with institutions in the US (18), closely followed by Europe (13), and India (1).

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.638
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.023
GPT teacher head0.255
Teacher spread0.231 · 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