Publication2026
Role of Machine Learning in Identity Verification
- Peace, Justice and Strong Institutions
- Partnerships for the Goals
- Good Governance and Security
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- International — held abroad
- Journal
- Combatting Digital Arrest Fraud and Identity Theft with AI and Decision Support Systems
- Pages
- 53-90
- Published
- 1 January 2026
- DOI
- 10.4018/979-8-3373-4149-1.ch003
- Scopus ID
- 105038483272
- Authors
- 9
- Open access
- No
- Citations
- 0
- International co-authorship
- Yes
- Co-author countries
- ID, IN, US
Classification
Every label below carries the reasoning it was assigned on, the confidence band it was assigned in, and what produced it. The rubric is published.
UN Sustainable Development Goals
16.4 Significantly reduce illicit financial and arms flows and combat all forms of organized crime
Book chapter on machine learning for identity verification examines supervised and deep learning models for biometric authentication, anomaly detection, and fraud prevention in banking and e-commerce.
- Moderate confidence
- The alignment is plausible and defensible but rests on an assumption a reasonable reviewer could decline. Published, and surfaced in the review queue for a human to confirm or override.
- Judged
- Judged against the published classification rubric, under the rubric and prompt versions recorded with the run that produced it.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
17.6 Enhance North-South, South-South and triangular cooperation on science, technology and innovation, and knowledge sharing
Structural signal: co-authorship outside India.
- High confidence
- The subject matter is a strong and direct inference from the record type, the funding or organising body, or the programme context, even where the title alone is thin. Example: an ICMR-funded project against SDG 3, on the strength of the agency.
- Rule-derived
- Emitted by a deterministic rule from structural signals rather than judged from the record’s text. The rule carries a version, so rule-derived and judged labels stay separable.
- Produced by
- sdg17-structural-v1, under kortex-publication-v1
Viksit Bharat @2047
vb-4 Good Governance and Security
Derived through the seeded SDG-to-Viksit-Bharat crosswalk from the primary SDG 16 label. Book chapter on machine learning for identity verification examines supervised and deep learning models for biometric authentication, anomaly detection, and fraud prevention in banking and e-commerce.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Each label above carries the instrument and the version that produced it. How each classification is reached.
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- 1
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Citing this record
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KIIT Deemed to be University. “Role of Machine Learning in Identity Verification”. Kortex.