CYBER CRIME DETECTION AND PREVENTION SYSTEMS

Abstract

Usage of internet and social media backgrounds
tends in the use of sending, receiving and
posting of negative, harmful, false or mean
content about another individual which thus
means Cyberbullying. Bullying over social
media also works the same as threatening,
calumny, and chastising the individual.
Cyberbullying has led to a severe increase in
mental health problems, especially among the
young generation. It has resulted in lower selfesteem, increased suicidal ideation. Unless some
measure against cyberbullying is taken, selfesteem and mental health issues will affect an
entire generation of young adults. Many of the
traditional machine learning models have been
implemented in the past for the automatic
detection of cyberbullying on social media. But
these models have not considered all the
necessary features that can be used to identify or
classify a statement or post as bullying. In this
paper, we proposed a model based on various
features that should be considered while
detecting cyberbullying and implement a few
features with the help of a bidirectional deep
learning model called BERT