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attack-and-anomaly-detection-in-iot-sensors-in-iot-sites-using-machine-learning-approaches icon attack-and-anomaly-detection-in-iot-sensors-in-iot-sites-using-machine-learning-approaches

Attack and Anomaly detection in the Internet of Things (IoT) infrastructure is a rising concern in the domain of IoT. With the increased use of IoT infrastructure in every domain, threats and attacks in these infrastructures are also growing commensurately. Denial of Service, Data Type Probing, Malicious Control, Malicious Operation, Scan, Spying and Wrong Setup are such attacks and anomalies which can cause an IoT system failure. In this paper, performances of several machine learning models have been compared to predict attacks and anomalies on the IoT systems accurately. The machine learning (ML) algorithms that have been used here are Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and Artificial Neural Network (ANN). The evaluation metrics used in the comparison of performance are accuracy, precision, recall, f1 score, and area under the Receiver Operating Characteristic Curve. The system obtained 99.4% test accuracy for Decision Tree, Random Forest, and ANN. Though these techniques have the same accuracy, other metrics prove that Random Forest performs comparatively better.

blog icon blog

pmarcelino.com blog posts

gc10-det-metallic-surface-defect-datasets icon gc10-det-metallic-surface-defect-datasets

This is the GC10-DET datasets of the upcoming paper " Deep Metallic Surface Defect Detection: the New Benchmark and Detection Network" The images of 10 common Metallic Surface defects were collected, and their pixel level ground-truth were labeled.

hackerrank-solution icon hackerrank-solution

hackerrank solutions github | hackerrank all solutions | hackerrank solutions for python |

nlp icon nlp

Tasks related to Natural Language Processing

rasa_restaurant_chat_bot icon rasa_restaurant_chat_bot

Contextual AI assistants with open source tools RASA. This is a restaurant chat bot. It uses Zomato API to get the restaurants information.

s2d2net icon s2d2net

The code for ImageNet CNN and CapsNet based hybrid model for steel defect recognition

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