Child brutality is one of the maximum abhorrent crimes winning in our society. Child Sexual Abuse (CSA) has handiest lately been publicly stated as a trouble in India. Around five kids die each day because of toddler abuse. Children who carouse in toddler abuse and forgot are nearly 60 percent much more likely to be arrested as buds, 30 percent much more likely to be arrested as a fully grown up person. Any shape of abuse or brutality to a toddler does be counted and cannot be forgotten. It influences the intellectual fitness of a toddler so greatly that it affects his future life. So, taking right measurements for saving each toddler from any form of brutality is a must. This paper advances a changed deep learning-primarily based totally LSTM set of rules is used for sexual goal detection and save the kid from abuse via no longer permitting the kid to go to the vicinity or with that individual. This CAP API could be capable of digging out and alert toddler misuse in real-time with none privateness breach. Threat detection primarily based totally handiest at the net surfing behaviour of clients. Child Abuse evaluation is primarily based totally on a multi-frequency dataset supplied via a prime Network Service Provider. CAP has been restricted to prevent sensual offenses towards kids at the darkish net and AI. Before it happens, stopping toddler sexual abuse has emerged as a serious problem and vital attempt from all regions of society: own circle of relatives caring, academy, community-primarily based totally treatment, and social trust. A progressive Sexual Intention literacy plan to conflict toddler sexual abuse is suggested to decrease adolescent crime at the darkish net. Every toddler, parent, teacher, or social employee who works with kids have to fete what toddler sexual abuse is and forestall it.
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14 November 2023
THE 4TH INTERNATIONAL CONFERENCE ON MATERIAL SCIENCE AND APPLICATIONS
3 December 2021
Ariyalur, India
Research Article|
November 14 2023
CAP: Child abuse risk prediction and prevention framework using AI and dark web
K. S. Guruprakash;
K. S. Guruprakash
a)
1
Department of Computer Science and Engineering, K.Ramakrishnan College of Engineering(Autonomous)
, Trichy, Tamil Nadu, India
a)Corresponding author: [email protected]
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V. Kalpana;
V. Kalpana
b)
2
Department of Computer Science and Engineering, K.Ramakrishnan College of Technology(Autonomous)
, Trichy, Tamil Nadu, India
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C. Selvarathi;
C. Selvarathi
c)
3
Department of Computer Science and Engineering, M.Kumarasamy College of Engineering(Autonomous)
, Karur, Tamil Nadu, India
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A. A. Shalini;
A. A. Shalini
d)
1
Department of Computer Science and Engineering, K.Ramakrishnan College of Engineering(Autonomous)
, Trichy, Tamil Nadu, India
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S. P. Shivani;
S. P. Shivani
e)
1
Department of Computer Science and Engineering, K.Ramakrishnan College of Engineering(Autonomous)
, Trichy, Tamil Nadu, India
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M. Sienaha
M. Sienaha
f)
1
Department of Computer Science and Engineering, K.Ramakrishnan College of Engineering(Autonomous)
, Trichy, Tamil Nadu, India
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K. S. Guruprakash
1,a)
V. Kalpana
2,b)
C. Selvarathi
3,c)
A. A. Shalini
1,d)
S. P. Shivani
1,e)
M. Sienaha
1,f)
1
Department of Computer Science and Engineering, K.Ramakrishnan College of Engineering(Autonomous)
, Trichy, Tamil Nadu, India
2
Department of Computer Science and Engineering, K.Ramakrishnan College of Technology(Autonomous)
, Trichy, Tamil Nadu, India
3
Department of Computer Science and Engineering, M.Kumarasamy College of Engineering(Autonomous)
, Karur, Tamil Nadu, India
a)Corresponding author: [email protected]
AIP Conf. Proc. 2822, 020260 (2023)
Citation
K. S. Guruprakash, V. Kalpana, C. Selvarathi, A. A. Shalini, S. P. Shivani, M. Sienaha; CAP: Child abuse risk prediction and prevention framework using AI and dark web. AIP Conf. Proc. 14 November 2023; 2822 (1): 020260. https://doi.org/10.1063/5.0173199
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