user_behaviour_classification

User Behaviour Classification using machine learning

In today’s World, Digitalisation is the trending picture among people because of its simplicity and ease of use where all data have to be accessed from anywhere within seconds. For that, all the data have to be kept in data centers which is to be connected to the internet. Data centers are the places where all the data about users, employees, company’s policies, system guide on which project works, etc is stored. This information is supposed to be kept secured from malicious users who want to steal data and misuse it. To protect that sensitive data from hackers, security departments have to point out the malicious users who are entering the data centers and vindicating the security of information. Parameters such as time of arrival, duty cycle, port, DNS backscatter, etc help us to detect the strange activity which concludes to be of malicious user.

Classifiers Used

1. KNN
2. Naive Bayes
3. SVM(Support Vector Machine)

run command

1. python3 knn.py

2. python3 knnscratch.py

3. python3 UserClassify.py

4. python3 naive.py

5. knn.py :- KNN Using python libraries and inbuilty functions.

6. knnscratch.py :- KNN using functions explicitely written.

7. UserClassify.py :- SVM using python libraries and functions.

8. naive.py :- Naive Bayes using python libraries and functions.