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Record W2284373869 · doi:10.1109/access.2016.2521727

Security Tradeoffs in Cyber Physical Systems: A Case Study Survey on Implantable Medical Devices

2016· article· en· W2284373869 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Access · 2016
Typearticle
Languageen
FieldEngineering
TopicWireless Body Area Networks
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCyber-physical systemComputer securityComputer sciencePhysical securityBlocking (statistics)Focus (optics)Risk analysis (engineering)BusinessComputer network

Abstract

fetched live from OpenAlex

The new culture of networked systems that offer everywhere accessible services has given rise to various types of security tradeoffs. In fact, with the evolution of physical systems that keep getting integrated with cyber frameworks, cyber threats have far more critical effects as they get reflected on the physical environment. As a result, the issue of security of cyber physical systems requires a special holistic treatment. In this paper, we study the tradeoff between security, safety, and availability in such systems and demonstrate these concepts on implantable medical devices as a case study. We discuss the challenges and constraints associated with securing such systems and focus on the tradeoff between security measures required for blocking unauthorized access to the device and the safety of the patient in emergency situations where such measures must be dropped to allow access. We analyze the up to date proposed solutions and discuss their strengths and limitations.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.274
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.304
Teacher spread0.274 · 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