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Record W2979593716 · doi:10.1093/cybsec/tyz013

The cyber-resilience of financial institutions: significance and applicability

2019· article· en· W2979593716 on OpenAlexafffund
Benoît Dupont

Bibliographic record

VenueJournal of Cybersecurity · 2019
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Resilience and Vulnerability Analysis
Canadian institutionsUniversité de MontréalInternational Centre for Comparative Criminology
FundersGlobal Risk Institute in Financial Services
KeywordsResilience (materials science)ThrivingComputer securityContext (archaeology)Risk managementCyber-attackBusinessRisk analysis (engineering)Computer scienceSociologyFinance

Abstract

fetched live from OpenAlex

Abstract The growing sophistication, frequency and severity of cyberattacks targeting financial sector institutions highlight their inevitability and the impossibility of completely protecting the integrity of critical computer systems. In this context, cyber-resilience offers an attractive complementary alternative to the existing cybersecurity paradigm. Cyber-resilience is defined in this article as the capacity to withstand, recover from and adapt to the external shocks caused by cyber risks. Resilience has a long and rich history in a number of scientific disciplines, including in engineering and disaster management. One of its main benefits is that it enables complex organizations to prepare for adverse events and to keep operating under very challenging circumstances. This article seeks to explore the significance of this concept and its applicability to the online security of financial institutions. The first section examines the need for cyber-resilience in the financial sector, highlighting the different types of threats that target financial systems and the various measures of their adverse impact. This section concludes that the “prevent and protect” paradigm that has prevailed so far is inadequate, and that a cyber-resilience orientation should be added to the risk managers’ toolbox. The second section briefly traces the scientific history of the concept and outlines the five core dimensions of organizational resilience, which is dynamic, networked, practiced, adaptive, and contested. Finally, the third section analyses three types of institutional approaches that are used to foster cyber-resilience in the financial sector (and beyond): (i) a thriving cybersecurity industry is promoting cyber-resilience as the future of security; (ii) standards bodies are embedding cyber-resilience into some of their cybersecurity standards; and (iii) regulatory agencies have developed a broad range of compliance tools aimed at enhancing cyber-resilience.

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)0.002
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0020.013
Scholarly communication0.0070.007
Open science0.0010.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.005
GPT teacher head0.223
Teacher spread0.219 · 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 designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations125
Published2019
Admission routes2
Has abstractyes

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