Year: 2024
Type: article
Abstract: The proliferation of fake social media profiles poses a significant threat to user security, trust, and the integrity of online platforms. This project proposes a novel system that leverages machine learning and blockchain technology to combat this growing problem. The system aims to accurately identify fake profiles by analyzing user behavior, content, and relevant metrics. Blockchain technology is employed to ensure data integrity, transparency, and immutability in profile verification and reporting. A secure and transparent reporting mechanism is developed using blockchain to log and track reports of fake profiles. The project aims to enhance user trust by reducing the prevalence of fake profiles and creating a more trustworthy online environment. The system also facilitates secure data sharing between platforms to enable collaboration in combating fake profiles while protecting user privacy. The expected results include an accurate detection system, an immutable reporting platform, and enhanced trust and security on social media platforms. This project represents a significant step forward in addressing the challenges posed by fake social media profiles and creating a more secure and trustworthy online ecosystem.
Authors: Shreyash Deshmukh, Gaurav Sati, Simran Kalaska, Mansha Gupta, Saurabh Vyas
Language: English
Topic: Spam and Phishing Detection
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4404620593