Omranys

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.

CNN

ConPan

ConPan: Analyze your Docker container in peace

coursera

debugger

phython

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

deep-learning-coursera-1

Deep Learning Specialization by Andrew Ng on Coursera

deep-learning-coursera-2

deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Deep_Learning

added all materials

Omranys/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.

Omranys/CNN

Omranys/ConPan

ConPan: Analyze your Docker container in peace

Omranys/coursera

Omranys/debugger

phython

Omranys/deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

Omranys/deep-learning-coursera-1

Deep Learning Specialization by Andrew Ng on Coursera

Omranys/deep-learning-coursera-2

Omranys/deep-learning-with-python-notebooks

Jupyter notebooks for the code samples of the book "Deep Learning with Python"

Omranys/Deep_Learning

added all materials

Omranys/DeepLearningProject

An in-depth machine learning tutorial introducing readers to a whole machine learning pipeline from scratch.

Omranys/genderComputer

Tool that tries to guess a person's gender based on their name and location

Omranys/grimoirelab-perceval

Send Sir Perceval on a quest to retrieve and gather data from software repositories.

Omranys/Java

All Algorithms implemented in Java

Omranys/Mogwai

Automatic translation from OCL to Gremlin

Omranys/neural-networks-and-deep-learning

This is my assignment on Andrew Ng's course “neural networks and deep learning”

Omranys/Projects-Papers

Omranys/Research

Omranys/SaudiOSS

قائمة بالمشاريع السعودية المفتوحة المصدر

Omranys/scikit-learn

scikit-learn: machine learning in Python

Omranys/sourcerer-app

🦄 Sourcerer app makes a visual profile from your GitHub and git repositories.

Omranys/TF_Files

Omranys/whowillwinksu

مشروع بسيط ممتاز للمبتدأين في تعلم تطوير تطبيقات الويب