不安全网络中的快速 UDP 互联网连接和传输控制协议:比较分析

IF 2.1 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS IET Smart Cities Pub Date : 2024-05-17 DOI:10.1049/smc2.12083
Andrew Simpson, Maitha Alshaali, Wanqing Tu, Muhammad Rizwan Asghar
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引用次数: 0

摘要

安全的数据传输和高效的网络性能是现代互联网的两个关键方面。传统上,传输层安全协议(TLS)/传输控制协议(TCP)被用于可靠和安全的网络通信。在过去十年中,在 UDP 基础上设计并实施了快速用户数据报协议(UDP)互联网连接 QUIC,试图提高互联网流量的安全性和效率。本文进行了真实世界平台调查,以评估 TLS/TCP 和 QUIC/UDP 在三种不同类型的流行网络攻击下保持通信、安全性和效率的情况。本文介绍了一系列有趣的发现,包括延迟、损失、服务器 CPU 利用率和服务器内存使用率,以全面了解这两种协议栈在执行恶意流量时的情况。更具体地说,在利用有限的 CPU 和内存资源实现短延迟和低数据包丢失率的效率方面,QUIC/UDP 在拒绝服务攻击中表现更佳,但在处理 MitM 攻击时,TLS/TCP 则超越了 QUIC/UDP。在安全性方面,TCP 的实施往往比 QUIC 更安全,但 QUIC 流量模式更难通过机器学习方法学习。我们希望这些见解能为未来网络和应用的协议选择提供参考,并为这两种协议栈的进一步发展提供启示。
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Quick UDP Internet Connections and Transmission Control Protocol in unsafe networks: A comparative analysis
Secure data transmission and efficient network performance are both key aspects of the modern Internet. Traditionally, Transport Layer Security (TLS)/Transmission Control Protocol (TCP) has been used for reliable and secure networking communications. In the past decade, Quick User Datagram Protocol (UDP) Internet Connections QUIC has been designed and implemented on UDP, attempting to improve security and efficiency of Internet traffic. Real‐world platform investigations are carried out in this paper to evaluate TLS/TCP and QUIC/UDP in maintaining communication, security and efficiency under three different types of popular cyber‐attacks. A set of interesting findings, including delay, loss, server CPU utilisation and server memory usage are presented to provide a comprehensive understanding of the two protocol stacks in performing malicious traffic. More specifically, in terms of the efficiency in achieving short delays and low packet loss rates with limited CPU and memory resources, QUIC/UDP performs better under Denial of Service attacks but TLS/TCP overtakes QUIC/UDP when handling MitM attacks. In terms of security, the implementation of TCP tends to be more secure than QUIC, but QUIC traffic patterns are harder to learn using machine learning methods. We hope that these insights will be informative in protocol selection for future networks and applications, as well as shedding light on the further development of the two protocol stacks.
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来源期刊
IET Smart Cities
IET Smart Cities Social Sciences-Urban Studies
CiteScore
7.70
自引率
3.20%
发文量
25
审稿时长
21 weeks
期刊最新文献
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