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Published on 24 January 2025
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Chen,H. (2025). Enhancing the Security of Transmission Control Protocol (TCP): Challenges and Solutions for Modern Network Threats. Applied and Computational Engineering,133,46-53.
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Enhancing the Security of Transmission Control Protocol (TCP): Challenges and Solutions for Modern Network Threats

Hongyi Chen *,1,
  • 1 Alcanta international college board, Guangzhou Nansha, China

* Author to whom correspondence should be addressed.

https://doi.org/10.54254/2755-2721/2025.20599

Abstract

Transmission Control Protocol (TCP), the backbone of internet communication, ensures reliable, connection-oriented data transmission. Despite its widespread use in areas such as email, web browsing, and file transfer, TCP faces significant security vulnerabilities stemming from its design era, which prioritized functionality over security. Common threats include TCP sequence number prediction, session hijacking, SYN flood attacks, and TCP Reset attacks. Existing mitigation strategies, such as TCP-AO, SSL/TLS encryption, and network-based security measures like IDS/IPS, have reduced risks but face challenges like performance overhead and compatibility issues. This study reviews the root causes of TCP vulnerabilities, evaluates existing solutions, and highlights gaps in addressing threats within modern network architectures. While current measures are effective to an extent, future research must explore advanced technologies such as quantum cryptography, blockchain-based authentication, and AI-driven anomaly detection to enhance TCP security and adaptability. This work underscores the urgent need for interdisciplinary collaboration and innovation to secure TCP in evolving digital ecosystems.

Keywords

TCP security, session hijacking, denial-of-service attack, SSL/TLS, protocol optimization

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Cite this article

Chen,H. (2025). Enhancing the Security of Transmission Control Protocol (TCP): Challenges and Solutions for Modern Network Threats. Applied and Computational Engineering,133,46-53.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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About volume

Volume title: Proceedings of the 5th International Conference on Signal Processing and Machine Learning

Conference website: https://2025.confspml.org/
ISBN:978-1-83558-943-4(Print) / 978-1-83558-944-1(Online)
Conference date: 12 January 2025
Editor:Stavros Shiaeles
Series: Applied and Computational Engineering
Volume number: Vol.133
ISSN:2755-2721(Print) / 2755-273X(Online)

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