Publication2026
Anomalies and Cyberattacks Detection Model in Resource Constrained IoT Networks
The record
- Type
- Publication
- Date
- 1 January 2026
- Level
- National
- Journal
- Lecture Notes in Networks and Systems
- Volume
- 1775 LNNS
- Pages
- 154-162
- Published
- 1 January 2026
- DOI
- 10.1007/978-3-032-14189-7_14
- Scopus ID
- 105028858117
- ISSN
- 23673370
- Authors
- 6
- Open access
- No
- Citations
- 0
- 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
4.4 Substantially increase the number of youth and adults with relevant skills for employment, decent jobs and entrepreneurship
Machine learning and SVM models for IoT security anomaly detection enhance cybersecurity skills and digital competency in resource-constrained networks.
- 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
9.5 Enhance scientific research, upgrade technological capabilities, and increase researchers and R&D spending
Novel two-stage detection framework with adaptive classifiers advances research capacity in network security and AI-driven threat identification.
- Produced by
- claude-haiku-4-5-20251001, under kortex-publication-v1
Viksit Bharat @2047
vb-3.2 Digital technology and artificial intelligence
Support Vector Machine and machine learning implementation for IoT security represents digital technology and AI research application.
- 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.
Evidence
Kortex hosts no documents. Evidence is an outbound link to the authority that holds it.
No outbound evidence link is recorded for this activity. The record below states which source it came from and when it was last read.
Provenance
Which source system this record came from, how many source rows were resolved into it, and when each was last read.
- Source rows resolved into this record
- 1
Each record carries the date Kortex last read it from its source system. That is a freshness date and not a verification: Kortex records what its sources say and when it read them, and it does not check those statements against any external authority. No claim on this site is described as verified, because none is.
Citing this record
This URL is stable. A record’s permalink is frozen when it is published and is not regenerated if its title is later corrected.
KIIT Deemed to be University. “Anomalies and Cyberattacks Detection Model in Resource Constrained IoT Networks”. Kortex.