Suppr超能文献

基于 SDN 技术的物联网场景下 DDoS 攻击缓解方法分类。

A Taxonomy of DDoS Attack Mitigation Approaches Featured by SDN Technologies in IoT Scenarios.

机构信息

LaTARC Research Lab (IFRN), Federal Institute of Education, Science and Technology of Rio Grande do Norte (IFRN), Natal, RN 59015-000, Brazil.

Department of Informatics and Applied Mathematics (DIMAp), Federal University of Rio Grande do Norte (UFRN), Natal, RN 59078-970, Brazil.

出版信息

Sensors (Basel). 2020 May 29;20(11):3078. doi: 10.3390/s20113078.

Abstract

The Internet of Things (IoT) has attracted much attention from the Information and Communication Technology (ICT) community in recent years. One of the main reasons for this is the availability of techniques provided by this paradigm, such as environmental monitoring employing user data and everyday objects. The facilities provided by the IoT infrastructure allow the development of a wide range of new business models and applications (e.g., smart homes, smart cities, or e-health). However, there are still concerns over the security measures which need to be addressed to ensure a suitable deployment. Distributed Denial of Service (DDoS) attacks are among the most severe virtual threats at present and occur prominently in this scenario, which can be mainly owed to their ease of execution. In light of this, several research studies have been conducted to find new strategies as well as improve existing techniques and solutions. The use of emerging technologies such as those based on the Software-Defined Networking (SDN) paradigm has proved to be a promising alternative as a means of mitigating DDoS attacks. However, the high granularity that characterizes the IoT scenarios and the wide range of techniques explored during the DDoS attacks make the task of finding and implementing new solutions quite challenging. This problem is exacerbated by the lack of benchmarks that can assist developers when designing new solutions for mitigating DDoS attacks for increasingly complex IoT scenarios. To fill this knowledge gap, in this study we carry out an in-depth investigation of the state-of-the-art and create a taxonomy that describes and characterizes existing solutions and highlights their main limitations. Our taxonomy provides a comprehensive view of the reasons for the deployment of the solutions, and the scenario in which they operate. The results of this study demonstrate the main benefits and drawbacks of each solution set when applied to specific scenarios by examining current trends and future perspectives, for example, the adoption of emerging technologies based on Cloud and Edge (or Fog) Computing.

摘要

物联网 (IoT) 近年来引起了信息与通信技术 (ICT) 社区的广泛关注。其中一个主要原因是这种范式提供的技术可用性,例如使用用户数据和日常对象进行环境监测。物联网基础设施提供的设施允许开发广泛的新业务模型和应用程序(例如,智能家居、智能城市或电子健康)。然而,对于需要解决以确保适当部署的安全措施仍存在一些担忧。分布式拒绝服务 (DDoS) 攻击是目前最严重的虚拟威胁之一,在这种情况下尤为突出,主要是因为它们易于执行。有鉴于此,已经进行了一些研究以寻找新策略以及改进现有的技术和解决方案。新兴技术的使用,例如基于软件定义网络 (SDN) 范式的技术,已被证明是缓解 DDoS 攻击的一种有前途的替代方法。然而,物联网场景的高粒度和 DDoS 攻击中探索的广泛技术使得寻找和实施新解决方案的任务极具挑战性。由于缺乏基准来帮助开发人员在为日益复杂的物联网场景设计新的缓解 DDoS 攻击的解决方案时,这个问题更加严重。为了填补这一知识空白,在本研究中,我们对最新技术进行了深入调查,并创建了一个分类法,该分类法描述和刻画了现有解决方案,并突出了它们的主要局限性。我们的分类法提供了一个综合的视角,了解解决方案部署的原因,以及它们在其中运行的场景。通过研究当前趋势和未来前景,例如采用基于云和边缘(或雾)计算的新兴技术,本研究的结果展示了每种解决方案在应用于特定场景时的主要优势和缺点。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验