Generative AI in Cybersecurity
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
For professional education, institutions may need to move from a predominantly detection-based response towards assessment architectures that both teach responsible AI use and preserve opportunities to verify human competence.
“For professional education, the implication is that institutions may need to move from a predominantly detection-based response towards assessment architectures that both teach responsible AI use and preserve opportunities to verify human competence (Sikos, 2025).”
From Between Co-Intelligence and Cognitive Offloading: Educators’ Perspectives from Dutch Academic Medical Settings on Generative AI, Critical Thinking, and Adult Professional Learning (2026) · cites this paper as Sikos, 2025
Cited by
Sorted by citations
Bruijn, K., & Vlachopoulos, D. (2026) · Education Sciences · doi:10.3390/educsci16091470
“For professional education, the implication is that institutions may need to move from a predominantly detection-based response towards assessment architectures that both teach responsible AI use and preserve opportunities to verify human competence (Sikos, 2025).”
- Authors
- Sikos, L. F.
- Corresponding author
- Sikos, Leslie F.
- ORCID
- Sikos, Leslie F.
- Venue
- SpringerBriefs in Cybersecurity
- Publisher
- Springer Nature Switzerland
- Published
- 2025
- ISSN
- 2193-973X (ISSN-L)
- 2193-9748
- OpenAlex
- W4416227518
- Cited by
- 1
- References
- 0
- Citations by year
- 2026: 1
- FWCI
- 1.37
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- Locations
- SpringerBriefs in cybersecurity (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Information Systems › Information and Cyber Security
- Keywords
- generative AI, cybersecurity, large language models
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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