Abstract: An amazing combination of cutting-edge data mining and machine learning methodologies to predict the level of safety feeling among Bangladeshi internet users, which is a significant departure in this subject. By leveraging cutting-edge algorithms and innovative data sources, this work provides previously unheard-of insights into how this demographic perceives online safety, shedding light on an essential yet underappreciated aspect of their digital lives. This exceptional study's original research increases the body of knowledge of online safety and sets the road for policy recommendations and intervention tactics that will enable Bangladesh to become a global leader in internet security.

Md. Safiul Alam, Anirban Roy, Partha Protim Majumder and Sharun Akter Khushbu. “Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.9 (2023). http://dx.doi.org/10.14569/IJACSA.2023.0140976

@article{Alam2023,
title = {Predicting the Level of Safety Feeling of Bangladeshi Internet users using Data Mining and Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140976},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140976},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {9},
author = {Md. Safiul Alam and Anirban Roy and Partha Protim Majumder and Sharun Akter Khushbu}
}