Adaptive and Semantic Predictions Model for Anomaly Detection in IoT Network Using Machine Learning

EasyChair Preprint 8003

Abstract

Adaptive and Sematic Prediction Model for Anomaly Detection in IoT Network using Machine Language is a widespread problem throughout the Iot paradigm. Through the increased use of IoT infrastructure in each sector, the hazards and vulnerabilities in these platforms are increasing in lockstep. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are the profound assaults and discrepancies of this kind might lead to IoT framework failure. Therefore, in this document, the results of a few AI models were compared to the ability to accurately predict attacks and anomalies on IoT frameworks. The AI (ML) calculations that have been utilized here are LR, SVM, RF, DT and ANN The assessment measurements utilized in the correlation of execution are exactness, accuracy, review and the f1 score. For DT, RF, and ANN, the framework achieved 99.4 percent test exactness. However, these procedures have similar exactness, different measurements demonstrate that the overall performance and exactness way up to the mark with RF model.Adaptive and Sematic Prediction Model for Anomaly Detection in IoT Network using Machine Language is a widespread problem throughout the Iot paradigm. Through the increased use of IoT infrastructure in each sector, the hazards and vulnerabilities in these platforms are increasing in lockstep. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are the profound assaults and discrepancies of this kind might lead to IoT framework failure. Therefore, in this document, the results of a few AI models were compared to the ability to accurately predict attacks and anomalies on IoT frameworks.

Keyphrases: Artificial Neural Network (ANN), Decision Tree (DT), Logistic Regression (LR), Random Forest (RF), Support Vector Machine (SVM)

@booklet{EasyChair:8003,
  author    = {R Kingsly Stephen and R Dakshan and Y Vinay Varma and R Sharanraj},
  title     = {Adaptive and Semantic Predictions Model for Anomaly Detection in IoT Network Using Machine Learning},
  howpublished = {EasyChair Preprint 8003},
  year      = {EasyChair, 2022}}