The Role and Place of Covid-19: An Opportunistic Avenue for Exponential World’s Upsurge in Cyber Crime
Bibliographic record
Abstract
An evidence-based analysis of COVID-19 suggests that the ailment is a bio-medically inclined natural mystic blowing through the world. To this end, this study focuses solely on the role the pandemic plays as an outbreak of cybercrime vector. The study presents a number of the world’s most recent cyber insecurity cases that accompanied the onset of the pandemic and findings were discussed within the context of situational opportunity theory of crime. It provides a framework for emergency management approach to protect global citizens and institutions from cyberattacks, as well as, mitigating the outbreak of the crime being propagated by the presence of the novel virus. Global sensitization and awareness programmes across various communities on the potential dangers of cyber insecurity accompanying the COVID-19 pandemic should be helpful. Of most significance, the fight against the invisible warfare should continue with high spirits of relentlessness until absolute peace, relief, resilience and normalcy are able to take root in the global communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.009 | 0.020 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".