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将软件工程流程集成到无线传感器网络中高效入侵检测系统的开发中。

Integrating Software Engineering Processes in the Development of Efficient Intrusion Detection Systems in Wireless Sensor Networks.

机构信息

Computer Science Department, Prince Sultan University, Riyadh 11586, Saudi Arabia.

Computer Science Department, The University of Jordan, Amman 11942, Jordan.

出版信息

Sensors (Basel). 2020 Mar 3;20(5):1375. doi: 10.3390/s20051375.

DOI:10.3390/s20051375
PMID:32138148
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7085656/
Abstract

Applying Software Engineering (SE) processes is vital to critical and complex systems including security and networking systems. Nowadays, Wireless Sensor Networks (WSNs) and their applications are found in many military and civilian systems which make them attractive to security attackers. The increasing risks and system vulnerabilities of WSNs have encouraged researchers and developers to propose many security solutions including software-based Intrusion Detection Systems (IDSs). The main drawbacks of current IDSs are due to the lack of clear, structured software development processes. Unfortunately, a substantial gap has been observed between WSN and SE research communities. Integrating SE and WSNs is an emerging topic that will be expanded as technology evolves and spreads in all life aspects. Consequently, this paper highlighted the importance of Requirement Engineering, Software Design, and Testing when developing IDSs for WSNs. Three software IDS designs were proposed in this study: Scheduling, Broadcast, and Watchdog designs. The three designs were compared in terms of consumed energy and network lifetime. Although the same IDS approach was used, but, by highlighting the design phase and implementing different designs, the network lifetime was increased by 73.6% and the consumed energy was reduced by 20% in some of the designs. This is a clear indication of how following a proper SE process could affect the performance of the IDS in WSN. Moreover, conclusions were drawn in regard to applying software engineering processes to IDSs to deliver the required functionalities, with respect to operational constraints, with an improved performance, accuracy and reliability.

摘要

将软件工程 (SE) 流程应用于包括安全和网络系统在内的关键和复杂系统至关重要。如今,无线传感器网络 (WSN) 及其应用在许多军事和民用系统中都有发现,这使得它们对安全攻击者具有吸引力。WSN 的风险和系统漏洞不断增加,促使研究人员和开发人员提出了许多安全解决方案,包括基于软件的入侵检测系统 (IDS)。当前 IDS 的主要缺点是由于缺乏清晰、结构化的软件开发流程。不幸的是,人们观察到 WSN 和 SE 研究社区之间存在很大差距。将 SE 和 WSN 集成是一个新兴话题,随着技术的发展和在所有生活方面的普及,这个话题将会得到扩展。因此,本文强调了在为 WSN 开发 IDS 时需求工程、软件设计和测试的重要性。本文提出了三种软件 IDS 设计:调度、广播和看门狗设计。这三种设计在能耗和网络寿命方面进行了比较。尽管使用了相同的 IDS 方法,但通过突出设计阶段并实施不同的设计,可以将网络寿命提高 73.6%,并在某些设计中降低 20%的能耗。这清楚地表明,遵循适当的 SE 流程如何影响 WSN 中 IDS 的性能。此外,还得出了关于将软件工程流程应用于 IDS 以提供所需功能的结论,同时考虑到操作约束,以提高性能、准确性和可靠性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/a33b227b8517/sensors-20-01375-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/7777b3283b92/sensors-20-01375-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/5d308f487cf7/sensors-20-01375-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/1ba8195102c5/sensors-20-01375-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/42ae114f6225/sensors-20-01375-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/62afbea33bb7/sensors-20-01375-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/bf8b0f69a852/sensors-20-01375-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/386cd632d244/sensors-20-01375-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/3f30b09fffa9/sensors-20-01375-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/a94466e519bf/sensors-20-01375-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/59b838639c6b/sensors-20-01375-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/a33b227b8517/sensors-20-01375-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/7777b3283b92/sensors-20-01375-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/5d308f487cf7/sensors-20-01375-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/1ba8195102c5/sensors-20-01375-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/42ae114f6225/sensors-20-01375-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/62afbea33bb7/sensors-20-01375-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/bf8b0f69a852/sensors-20-01375-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/386cd632d244/sensors-20-01375-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/3f30b09fffa9/sensors-20-01375-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/a94466e519bf/sensors-20-01375-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/59b838639c6b/sensors-20-01375-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ca54/7085656/a33b227b8517/sensors-20-01375-g011.jpg

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