Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection
Saved in:
| Published in: | PLOS ONE |
|---|---|
| Format: | Online Article RSS Article |
| Published: |
2026
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1864030192239902723 |
|---|---|
| collection | WordPress RSS FRELIP Feed Integration |
| container_title | PLOS ONE |
| description | |
| discipline_display | Engineering & Technology |
| discipline_facet | Engineering & Technology |
| format | Online Article RSS Article |
| genre | Journal Article |
| id | rss_article:10981 |
| institution | FRELIP |
| journal_source_facet | PLOS ONE |
| publishDate | 2026 |
| publishDateSort | 2026 |
| record_format | rss_article |
| spellingShingle | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection Cybersecurity, Cryptography and Privacy Computer Science & IT Engineering & Technology |
| sub_discipline_display | Computer Science & IT |
| sub_discipline_facet | Computer Science & IT |
| subject_display | Cybersecurity, Cryptography and Privacy Computer Science & IT Engineering & Technology Cybersecurity, Cryptography and Privacy Computer Science & IT Engineering & Technology |
| subject_facet | Cybersecurity, Cryptography and Privacy Computer Science & IT Engineering & Technology |
| title | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_auth | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_full | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_fullStr | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_full_unstemmed | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_short | Retraction: Enhancing IoT cybersecurity through lean-based hybrid feature selection and ensemble learning: A visual analytics approach to intrusion detection |
| title_sort | retraction: enhancing iot cybersecurity through lean-based hybrid feature selection and ensemble learning: a visual analytics approach to intrusion detection |
| topic | Cybersecurity, Cryptography and Privacy Computer Science & IT Engineering & Technology |
| url | https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0346538 |