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Established different method using Machine Learning Techniques for given IoT Botnet dataset by Data Preparation and Data analysis to identify and solve the problem

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IoT Botnet Detection using ML Techniques

The BoT-IoT dataset was created by designing a realistic network environment in the Cyber Range Lab of UNSW Canberra

Botnet attack is a type of cyber attack carried out by a group of internet-connected devices controlled by a malicious actor

Established different method using Machine Learning Techniques for given IoT Botnet dataset by Data Preparation and Data analysis to identify and solve the problem

Data analysis & preparation is done based on 5% of 10 best features of the entire dataset

5% Subset contains the most features of any processed set or subset of Bot-IoT with 16 independent features and 3 dependent features

16 independent feature contain the Argus network flow features and the additional calculated features

5% Subset is divided into two Training & Test CSV files, each containing its own header row with feature names

Train & Test Dataset link: https://cloudstor.aarnet.edu.au/plus/s/umT99TnxvbpkkoE?path=%2FCSV%2FTraning%20and%20Testing%20Tets%20(5%25%20of%20the%20entier%20dataset)%2F10-best%20features

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Established different method using Machine Learning Techniques for given IoT Botnet dataset by Data Preparation and Data analysis to identify and solve the problem

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