First and Last Name/s of Presenters

Geetanjali KakdaFollow

Mentor/s

Dr. Eman Abdelfattah

Participation Type

Poster

Abstract

A firewall is a type of security mostly located at the entry and exit points of a network. This is necessary to improve the security of the network and defend against cyber threats. This study aims to classify the internet traffic using different Machine Learning classification models into four categories based on 11 features. The models applied are – K-Nearest Neighbor, SGD, Decision Tree, Random Forest , XGBoost, Support Vector Machine. The XGBoost model achieved the highest accuracy, recall, precision,F1score. Decision Tree has the least time complexity.

College and Major available

Computer Science & IT MS

Location

Digital Commons & West Campus 2nd Floor University Commons

Start Day/Time

4-28-2023 12:00 PM

End Day/Time

4-28-2023 2:00 PM

Students' Information

Geetanjali Kakda, Master's in Computer Science and Information Technology, Graduation - Dec 2023, email - kakdag@mail.sacredheart.edu.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.

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Apr 28th, 12:00 PM Apr 28th, 2:00 PM

Classifying Action of Internet Firewall Using Machine Learning Models

Digital Commons & West Campus 2nd Floor University Commons

A firewall is a type of security mostly located at the entry and exit points of a network. This is necessary to improve the security of the network and defend against cyber threats. This study aims to classify the internet traffic using different Machine Learning classification models into four categories based on 11 features. The models applied are – K-Nearest Neighbor, SGD, Decision Tree, Random Forest , XGBoost, Support Vector Machine. The XGBoost model achieved the highest accuracy, recall, precision,F1score. Decision Tree has the least time complexity.

 

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