Publication2022
MFBFST: Building a stable ensemble learning model using multivariate filter-based feature selection technique for detection of suspicious URL
The record
- Type
- Publication
- Date
- 1 January 2022
- Level
- National
- Journal
- Procedia Computer Science
- Volume
- 218
- Pages
- 1668-1681
- Published
- 1 January 2022
- DOI
- 10.1016/j.procs.2023.01.145
- Scopus ID
- 85162108962
- ISSN
- 18770509
- Authors
- 2
- Open access
- Yes
- Citations
- 14
- International co-authorship
- No
- Co-author countries
- IN
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 Promote peaceful and inclusive societies for sustainable development, provide access to justice for all and build effective, accountable and inclusive institutions at all levels
Malicious URL detection using ensemble machine learning directly addresses cybercrime prevention and digital security.
- 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.
- 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
Viksit Bharat @2047
vb-4.4 Public safety, cybersecurity and national security
Cybersecurity research for fraud and malware prevention supports digital security and online safety.
- 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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- Source rows resolved into this record
- 1
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Citing this record
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KIIT Deemed to be University. “MFBFST: Building a stable ensemble learning model using multivariate filter-based feature selection technique for detection of suspicious URL”. Kortex.