CUSTOMER CHURN PREDICTION
Abstract & Details
Research Area
Computer Engineering
Keywords
churn management
wireless telecommunication
data mining
decision tree
neural network
big data
cloud computing
Abstract
The popularity of using Internet contains some risks of network attacks. Intrusion detection is one major research problem in network security, whose aim is to identify unusual access or attacks to secure internal networks. In literature, intrusion detection systems have been approached by various machine learning techniques. In this literature, we propose a real-time intrusion detection approach using a supervised machine learning technique. Our approach is simple and efficient, and can be used with many machine learning techniques. We applied different well-known machine learning techniques to evaluate the performance of our IDS approach. Our experimental results show that the Decision Tree technique can outperform the other techniques. Therefore, we further developed a real-time intrusion detection system (RT-IDS) using the Decision Tree technique to classify on-line network data as normal or attack data.
License
This work is licensed under a Creative
Commons
Attribution-ShareAlike 4.0 International License.
Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Ruhul Phadatare | SKN Sinhgad Institute of Technology, Lonavala, Pune |
| 2 | Gaurav Khedkar | SKN Sinhgad Institute of Technology, Lonavala, Pune |
| 3 | Harshal Patil | SKN Sinhgad Institute of Technology, Lonavala, Pune |
| 4 | Sumeet Survase | SKN Sinhgad Institute of Technology, Lonavala, Pune |
| 5 | Harsh Shilimkar | SKN Sinhgad Institute of Technology, Lonavala, Pune |
How to Cite
Use the following formats to cite this article in your research.
APA Style
Phadatare, Ruhul, Khedkar, Gaurav, Patil, Harshal, Survase, Sumeet, & Shilimkar, Harsh (2023). CUSTOMER CHURN PREDICTION. International Journal of Advance Research and Innovative Ideas In Education, 9(6), 2557-2561.
MLA Style
Phadatare, Ruhul, et al. "CUSTOMER CHURN PREDICTION." International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 6, 2023, pp. 2557-2561.
IEEE Style
Ruhul Phadatare, Gaurav Khedkar, Harshal Patil, Sumeet Survase, and Harsh Shilimkar, "CUSTOMER CHURN PREDICTION," International Journal of Advance Research and Innovative Ideas In Education, vol. 9, no. 6, pp. 2557-2561, 2023.
Vancouver Style
Phadatare Ruhul, Khedkar Gaurav, Patil Harshal, Survase Sumeet, Shilimkar Harsh. CUSTOMER CHURN PREDICTION. International Journal of Advance Research and Innovative Ideas In Education. 2023;9(6):2557-2561.
Harvard Style
Phadatare, Ruhul, Khedkar, Gaurav, Patil, Harshal, Survase, Sumeet, & Shilimkar, Harsh (2023) 'CUSTOMER CHURN PREDICTION', International Journal of Advance Research and Innovative Ideas In Education, 9(6), pp. 2557-2561.
Chicago Style
Phadatare, Ruhul, et al. "CUSTOMER CHURN PREDICTION." International Journal of Advance Research and Innovative Ideas In Education 9, no. 6 (2023): 2557-2561.
Turabian Style
Phadatare, Ruhul, et al. "CUSTOMER CHURN PREDICTION." International Journal of Advance Research and Innovative Ideas In Education 9, no. 6 (2023): 2557-2561.
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