Deep learning based content moderation system to stop cybercrime caused by social media

Sachin Bhosale; Neha Shinde; Shreya Laware; Satyam Wable

Deep learning based content moderation system to stop cybercrime caused by social media

May 2024

Vol-10, Issue-3

Paper ID: 24050

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Information Technology

Keywords

Cybercrimes Social media platforms Content discovery system Image auditing Text extraction Video auditing Convolutional neural network (CNN) Machine learning Deep learning Vicious content detection Pornography Terrorism Cyber-bullying Sexual harassment Fraud detection

Abstract

Crime rates in moment’s world have increased due to content posted on colorful social media platforms leading to cybercrimes. The proportion of crimes in this order increased from3.7 in 2020 to3.9 in 2021. During 2021,60.8 of cybercrimes reported were for fraud( 32,230 cases out of 52,974 cases) followed by sexual exploitation, with8.6( 4,555 cases) and highway robbery with5.4( 2,883 cases). In this paper we present a largely effective content discovery system, design for processing content uploaded daily to colorful social media platforms. This paper isn't only limited to image auditing but also composition and videotape auditing. The main ideal behind this idea is to check the vicious content set up on social media and thereby reduce the crime rate. This system uses a convolutional neural network( CNN) to prize textbook from images as well as descry and classify all videotape frames. It's a combination of CNN and other machine literacy and deep literacy ways. The proposed system includes transferring instant cautions to the Cyber Crime Cell if any vicious content like pornography, terrorism, cyber-bullying, etc. is detected. therefore, this system detects vicious exertion and will help terrorism, vilification and sexual importunity in future.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Sachin Bhosale	Pravara Rural Engineering College, Loni.
2	Neha Shinde	Pravara Rural Engineering College, Loni.
3	Shreya Laware	Pravara Rural Engineering College, Loni
4	Satyam Wable	Pravara Rural Engineering College, Loni.

How to Cite

Use the following formats to cite this article in your research.

APA Style

Bhosale, Sachin, Shinde, Neha, Laware, Shreya, & Wable, Satyam (2024). Deep learning based content moderation system to stop cybercrime caused by social media. International Journal of Advance Research and Innovative Ideas In Education, 10(3), 2877-2881.

MLA Style

Bhosale, Sachin, et al. "Deep learning based content moderation system to stop cybercrime caused by social media." International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, 2024, pp. 2877-2881.

IEEE Style

Sachin Bhosale, Neha Shinde, Shreya Laware, and Satyam Wable, "Deep learning based content moderation system to stop cybercrime caused by social media," International Journal of Advance Research and Innovative Ideas In Education, vol. 10, no. 3, pp. 2877-2881, 2024.

Vancouver Style

Bhosale Sachin, Shinde Neha, Laware Shreya, Wable Satyam. Deep learning based content moderation system to stop cybercrime caused by social media. International Journal of Advance Research and Innovative Ideas In Education. 2024;10(3):2877-2881.

Harvard Style

Bhosale, Sachin, Shinde, Neha, Laware, Shreya, & Wable, Satyam (2024) 'Deep learning based content moderation system to stop cybercrime caused by social media', International Journal of Advance Research and Innovative Ideas In Education, 10(3), pp. 2877-2881.

Chicago Style

Bhosale, Sachin, et al. "Deep learning based content moderation system to stop cybercrime caused by social media." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 2877-2881.

Turabian Style

Bhosale, Sachin, et al. "Deep learning based content moderation system to stop cybercrime caused by social media." International Journal of Advance Research and Innovative Ideas In Education 10, no. 3 (2024): 2877-2881.