# Enhancing Cache Robustness in Information-Centric Networks: Per-Face Popularity Approaches
###### Abstract  
Information-Centric Networking (ICN) is a new paradigm of network architecture that focuses on content rather than hosts as first-class citizens of the network. As part of these architectures, in-network storage devices are essential to provide end users with close copies of popular content, to reduce latency and improve the overall experience for the user but also to reduce network congestion and load on the content producers. To be effective, in-network storage devices, such as content storage routers, should maintain copies of the most popular content objects. Adversaries that wish to reduce this effectiveness can launch cache pollution attacks to eliminate the benefit of the in-network storage device caches. Therefore, it is crucial to protect these devices and ensure the highest hit rate possible. This paper demonstrates Per-Face Popularity approaches to reducing the effects of cache pollution and improving hit rates by normalizing assessed popularity across all faces of content storage routers. The mechanisms that were developed prevent consumers, whether legitimate or malicious, on any single face or small number of faces from overwhelmingly influencing the content objects that remain in the cache. The results demonstrate that per-face approaches generally have much better hit rates than currently used cache replacement techniques. N 202318 September 202318 December 202318 September 202318 December 20231  
Data-Oriented Network (DONA) [4], Network of Information (NetInf) [5, 6], Content-Centric Networking (CCN) [7, 8], and Named Data Networking (NDN) [9]. Many interesting research challenges exist to provide the desired features of ICN. In this paper, we discuss technology related to in-network caching of data, which is a key feature to lowering latency and overall network congestion, using technology at the network layer. While in-network storage devices in ICN seek to provide similar services to those that Content Distribution (or Delivery) Networks (CDNs) [10] do today, in-network storage devices do so at the network layer and take advantage of various optimizations therein. In-network caching is discussed in a variety of recent research studies as a primary goal in ICN and NDN [11, 12, 13]. Given the pervasiveness of in-network storage devices in ICN architectures, these devices are prime targets for malicious users. In terms of in-network caching of popular data, an attacker would seek to reduce or remove any benefit experienced by the presence of in-network storage devices, such as content routers. An attack well suited for this type of service degradation is the cache pollution attack [14]. In this type of attack, the malicious attempt is to push truly popular content objects out of the cache in favor of less popular content objects. Ultimately, the goal is to reduce the hit rate experienced by users, such that the content that is genuinely popular is rarely or never in the content store of the in-network storage devices. These types of attacks are not new--they have been experienced for years in the current IP-based Internet, such as in CDNs and other situations involving proxy caching servers [15]. However, these attacks will certainly be even more of a threat in an architecture where in-network storage is part of the fundamental fabric of the network and not just an overlay. Several proposed solutions for preventing or reducing the effects of cache pollution attacks in ICN exist. However, most are insufficient for various reasons. Some lack adequate security and can be easily overcome, such as CacheShield [16]. Others assume all abnormal behaviors follow uniform distributions [17], and still others require significant computational or memory overhead, such as ANFIS [18]. Most current techniques attempt to detect attacks, which is often difficult when attackers employ various smart attacks. Additionally, these techniques can yield false positives if a user is even a little more aggressive in their request frequencies, and they may punish them even though they were not being malicious.