Open AccessOnline Child Predator Detection Using ML (Research Paper)
Author(s) -
Prof. Swati Gade,
Utkarsha Bhadre,
Tabassum Shaikh,
Mahesh Bangar,
Sarika Waghmode
Publication year - 2022
Publication title -
international journal for research in applied science and engineering technology
Language(s) - English
Resource type - Journals
ISSN - 2321-9653
DOI - 10.22214/ijraset.2022.40832
Subject(s) - the internet , psychology , task (project management) , internet privacy , predator , social psychology , computer science , computer security , predation , world wide web , engineering , ecology , biology , systems engineering
Proficient analysts should all the more completely comprehend the risks of online sexual sales and manners by which to shield youth from sexual stalkers who utilize the Internet. Albeit the Internet has numerous positive angles, quite possibly the most malicious aspect is its expected use for online sexual predation. The Internet addresses a medium that permits sexual stalkers admittance to innumerable kids in a moderately mysterious climate. The primary goal of our task is to distinguish kid hunter base on remarks and post of web-based media account and send hunter record to digital cell admin. A late public review demonstrated that around one out of five youth are requested for sex over the Internet yearly (Finkelhor, Mitchell, and Wolak, 2000; Mitchell, Finkelhor, and Wolak, 2001). This task report presents our present advancement to empower the formation of the framework. Thus, with the created framework, youngster hunter accounts recognition any report to administrator for additional activity. Index Terms: ML, dataset, Training Module, Predator.