A network coding transmission strategy for preventing eavesdropping attacks.

Area of Science:

• Computer Science
• Information Security
• Network Engineering

Background:

• Traditional secure network coding methods often impose restrictive preconditions, such as limiting the eavesdropping channel set or embedding encryption technology, which can hinder practical applications.
• Eavesdropping attacks pose a significant threat to the confidentiality of data transmitted over networks, particularly in single-source multicast scenarios.

Purpose of the Study:

• To propose a novel transmission strategy based on random linear network coding to prevent eavesdropping attacks in single-source multicast networks.
• To develop a method that does not require restrictions on the eavesdropping channel set or the embedding of encryption technology.
• To ensure successful data decoding for legitimate sinks while making it difficult for eavesdroppers to decode the information.

Main Methods:

• The proposed strategy divides the data transmission process into three distinct phases.
• Global encoding vectors are separated from the encoded data transmitted over the channel.
• Layered network technology is employed for rigorous demonstration of the method's feasibility and security analysis.

Main Results:

• The strategy enables successful data decoding at the sink node.
• It significantly increases the difficulty for eavesdroppers to meet decoding conditions, especially without network topology knowledge.
• Theoretical analysis and simulation results validate the effectiveness and security of the proposed method.

Conclusions:

• The developed random linear network coding strategy offers a practical and secure solution for preventing eavesdropping in multicast networks.
• The method effectively decouples encoding vectors from data, enhancing security without compromising usability.
• The findings provide a robust framework for secure data transmission in environments vulnerable to eavesdropping.