Mitigating content poisoning attacks in named data networking: a survey of recent solutions, limitations, challenges and future research directions

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Review Pub Date : 2024-12-20 DOI:10.1007/s10462-024-10994-x
Syed Sajid Ullah, Saddam Hussain, Ihsan Ali, Hizbullah Khattak, Spyridon Mastorakis
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Abstract

Named Data Networking (NDN) is one of the capable applicants for the future Internet architecture, where communications focus on content rather than providing content. NDN implements Information-Centric Networking (ICN) with its unique node structure and significant characteristics such as built-in mobility support, multicast support, and efficient content distribution to end-users. It has several key features, including inherent security, that protect the content rather than the communication channel. Despite the good features that NDN provides, it is nonetheless vulnerable to a variety of attacks, the most critical of them is the Content Poisoning Attack (CPA). In this survey, the existing solutions presented for the prevention of CPA in the NDN paradigm have been critically analyzed. Furthermore, we also compared the suggested schemes based on latency, communication overhead, and security. In addition, we have also shown the possibility of other possible NDN attacks on the suggested schemes. Finally, we adds some open research challanges.

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命名数据网络(NDN)是未来互联网架构的有力申请者之一,在这种架构中,通信的重点是内容而不是提供内容。NDN 实现了以信息为中心的网络(ICN),具有独特的节点结构和重要特性,如内置移动性支持、组播支持和向终端用户高效分发内容。它有几个关键特性,包括固有的安全性,可以保护内容而不是通信通道。尽管 NDN 具有这些良好特性,但它仍然容易受到各种攻击,其中最严重的攻击是内容中毒攻击 (CPA)。在本调查中,我们对 NDN 范例中预防 CPA 的现有解决方案进行了批判性分析。此外,我们还比较了基于延迟、通信开销和安全性的建议方案。此外,我们还展示了针对建议方案的其他可能的 NDN 攻击的可能性。最后,我们补充了一些有待解决的研究难题。
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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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