Logistic Regression Ensemble Classifier for Intrusion Detection System in Internet of Things
Silpa Chalichalamala, Niranjana Govindan, Ramani Kasarapu, Jose Manuel Molina López · 2023
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Description
Silpa Chalichalamala and co-authors present a 2023 computer security paper on guarding the Internet of Things. Connected home, health, and transport devices are handy but open fresh doors to hackers. The authors build an intrusion detection system that learns to spot attacks in network traffic.
Their system blends two known methods, AdaBoost and random forests, into one ensemble built around logistic regression. They balance skewed training data with synthetic samples and prune useless features before training. On two public test sets of device traffic, the system scored almost perfect accuracy, beating earlier designs on most measures. The work points toward stronger automatic defenses for the growing web of everyday connected objects.
Catalog record
| CREATOR | Silpa Chalichalamala, Niranjana Govindan, Ramani Kasarapu, Jose Manuel Molina López |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |