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Research on Online Social Network Information Leakage-Tracking Algorithm Based on Deep Learning.

¹School of Intelligent Manufacturing and Information, Jiangsu Shipping College, Nantong, Jiangsu 226010, China.

Computational Intelligence and Neuroscience

|July 8, 2022

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This study introduces a novel deep learning algorithm for tracking information leakage in online social networks. The proposed digital fingerprinting method significantly enhances accuracy and performance compared to traditional approaches.

Area of Science:

Computer Science
Information Security
Network Engineering

Background:

Online social networks are growing rapidly, leading to complex data and increasing privacy disclosure risks.
Existing privacy algorithms like encryption and differential privacy do not fully address these disclosure issues.
Effective tracking of information leakage is crucial for user safety and network integrity.

Purpose of the Study:

To develop an advanced algorithm for accurately detecting and tracking information leakage in large-scale online social networks.
To enhance user content perception and protection against privacy breaches.
To improve the efficiency and scalability of network information leakage tracking.

Main Methods:

Utilized deep convolution neural networks for accurate searching and filtering of online social network content.

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Implemented compressed sensing technology to randomly disturb graphics and data for enhanced privacy.

Proposed a digital fingerprint-based network information leakage-tracking algorithm using unique user identification and social network topology coding.

Main Results:

The proposed algorithm demonstrated a maximum accuracy improvement of approximately 10% over traditional methods.
Recall index showed an improvement of 5-8% compared to traditional algorithms.
Overall performance saw a significant enhancement of about 50% compared to traditional approaches.

Conclusions:

The developed deep learning-based algorithm offers superior accuracy and efficiency in tracking network information leakage.
Digital fingerprinting combined with deep learning provides a robust solution for identifying information leakers.
The findings suggest a more effective approach to safeguarding user privacy in complex online social networks.