Optimized Hybrid Model Using Machine Learning to Combat the Prevalence of Cybercrime

In this contemporary era, internet has become the mode of communication and has changed the life style of individuals with advancements in technology. Modern electronic gadgets made us more dependent on it directly or indirectly for most of people regardless of their age. The tremendous attain of the internet, the speedy unfold of mobile data, and consequently the extensive use of online forums has paved the way for online Crime. Cybercrime and victimization of female gender are excessive and it poses a serious threat to the safety of an individual as an entire. Smart devices with web connections and social media platforms support to explore huge information including objectionable materials. These offensive contents include pornography, cyberbullying, sexual abuse and threats, ferocity, gambling endanger more among ladies and youngsters on the net. These unsolicited information's has an impact to increases the vulnerability of crime against women and among younger age group children including adolescents. Cyber parental control is a method that affords a safe environment in the internet world for individual in particular women and youngsters to work in a controlled atmosphere for accessing internet with a healthy soul and mind. Considering the above context, the objective of this systematic review is two-fold, (1) To explore and understand various women related issues due to use of virtual platform, and (2) To analyze and propose an effective system for cyber parental control, the probable digital solution to reduce the vulnerability against cybercrime in specific among the feminine victim. The proposed model seeks to improve parental control by blocking offensive content. Despite the fact that pop-up messages may contain audio, video, or text, the suggested model can only handle text data. Future developments of the work could include handling multimedia data of various sizes and the ability to categorize the material. Furthermore, neural network-based algorithms ...