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Are critical success factors for cybersecurity just technical issues Cybersecurity management and the human factor

2023· article· en· W4385319554 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.

Bibliographic record

VenuePressacademia · 2023
Typearticle
Languageen
FieldComputer Science
TopicInformation and Cyber Security
Canadian institutionsMcGill University
Fundersnot available
KeywordsData breachComputer securityBusinessVulnerability (computing)HackerReputationHuman errorHarmInformation technologyRisk analysis (engineering)Computer science

Abstract

fetched live from OpenAlex

Purpose- With the rapid advancement of information and communication technologies, businesses are facing growing security risks. The prevalence, intensity, and complexity of cyber attacks worsen these vulnerabilities, leading to a rising focus on cybersecurity. Enterprises exposed to such cyberattacks might not only face considerable financial losses but also experience data breaches, operational interruptions, harm to their reputation, regulatory penalties, legal expenses, reduced competitive standing, and increased insurance premiums. In this concept study discusses the importance of human factors in cybersecurity management. While organizations spend billions on information technology systems and software to detect and prevent cyber threats, individuals play a critical role in managing these risks. Methodology- Through a review of literature and statistical data, study examines the factors contributing to cybersecurity breaches, the allocation of resources to address them, and proposes potential solutions. Findings- In the workplace, most research on cybersecurity focuses on employees as the most important source of vulnerability. In the literature review, it is understood that an employee’s carelessness and lack of awareness pose the greatest risk to cybersecurity. However, businesses often fail to show sufficient attention to human behavior in their efforts to keep organizational data secure and to plan security strategies. It is important to note that effective cybersecurity management requires not only technical controls but also the management of human factors. Meanwhile, security expenditures in enterprises are often disproportionately allocated to technology investments, with 97% being spent on technology investments, despite the fact that over 85% of breaches are attributable to human factors. Conclusion- In the literature review, it is understood that cybersecurity management is not only related to technical controls, but also the management of human factors is of critical importance. The management of individuals is also an essential cybersecurity responsibility. It is important to adopt a holistic approach to cybersecurity management includes both technical and human perspectives. Cybersecurity awareness has significant benefits for businesses to effectively manage cybersecurity which can be achieved by developing appropriate training programs and foster a cybersecurity culture. Keywords: Cybersecurity, cybersecurity management, cybersecurity awareness, technology investments, human factor JEL Codes: M12, M15, L86

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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.766
Threshold uncertainty score0.767

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 studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
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 head0.044
GPT teacher head0.344
Teacher spread0.300 · 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