物联网系统中以内容为中心的移动网络的高效缓存安全方法

IF 1.5 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Security and Privacy Pub Date : 2023-01-23 DOI:10.1002/spy2.294
Zhuang Du, M. Obaidat, Guowei Wu, K. Hsiao
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引用次数: 0

摘要

随着物联网的发展,基于IP的网络架构已经难以支撑物联网的发展。以内容为中心的移动网络(CCMN)模型是基于命名内容来摆脱地址空间的稀缺性,在中间节点缓存内容以提供高效的数据传输,可以解决物联网的发展瓶颈。网络内缓存是实现CCMN实际部署的关键因素。此外,它还受到缓存污染攻击(CPA)的严重安全威胁,这种攻击可以篡改内容的分布,降低内置缓存的优势。此外,移动设备的身份和信任机制也是阻碍CCMN部署的重要因素。然而,由于内置缓存的普遍性、移动性和异构性等特点,现有的缓存安全机制不能直接应用,这给设计针对CPA的缓存安全机制带来了新的挑战。在本文中,我们提出了一种针对CCMN的轻量级CPA检测和防御方法。我们首先将CPA的攻击和防御过程建模为一个动态博弈,从而优化攻击检测的性能。然后,采用流行度分析检测CPA,并通过逻辑回归算法准确估计当前网络和攻击状态。我们的设计还可以智能地维护身份和信任机制。最后,我们设计了一个惩罚机制来对付攻击者。大量的仿真结果表明,我们的方法可以有效地检测CPA,有效地减轻CPA的影响。与最先进的方法相比,我们的博弈模型可以将局部中断攻击和虚假局部攻击的影响分别降低60%和30%。当博弈达到纳什均衡时,我们的模型可以将CPA对缓存命中率的影响平均降低55%。
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An efficient caching security approach for content‐centric mobile networks in internet of things systems
With the expansion of internet of things (IoT), the IP‐based network architecture has been difficult to support the development of IoT. Content‐centric mobile networking (CCMN) models are based on naming the content to get rid of address‐space scarcity, caching the content at intermediate nodes to provide efficient data delivery, which can solve the development bottleneck of IoT. The in‐network caching is a key factor to enable practical deployments of CCMN. And it is also subject to serious security threats of cache pollution attacks (CPA), which can tamper the distribution of content and reduce the advantages of built‐in cache. In addition, the identity and trust mechanism of mobile devices are also important factors hindering the deployment of CCMN. However, existing caching security mechanisms cannot be applied directly, because the features of the built‐in cache, including ubiquity, mobility, and heterogeneity, bring new challenges on designing the caching security mechanism against CPA. In this article, we propose a lightweight CPA detection and defense approach for CCMN. We first model the attack and defense process of CPA as a dynamic game, which can optimize the performance of the attack detection. Then, we adopt popularity analysis to detect CPA, and accurately estimate the current network and attack state by a logical regression algorithm. Our design can also intelligently maintain the identity and trust mechanism. Finally, we design a punishment mechanism to deal with the attackers. Extensive simulations demonstrate that our approach can detect CPA efficiently, mitigate the impact of CPA effectively. Our game model can reduce the impact of locality‐disruption attack and false‐locality attack by 60% and 30%, respectively, compared with the state‐of‐the‐art methods. When the game reaches Nash equilibrium, our model can reduce the impact of CPA on cache hit ratio by 55% on average.
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