CAPnet: A Defense Against Cache Accounting Attacks on Content Distribution Networks
This addresses security vulnerabilities in hybrid CDNs that incentivize cache participation, preventing fraudulent reward collection by malicious actors, though it is an incremental improvement focused on a specific domain.
The paper tackles the problem of cache accounting attacks in peer-assisted content distribution networks (CDNs), where malicious caches can falsely claim content transfers to collect rewards. The result is CAPnet, a lightweight cache accountability puzzle that bounds attack effectiveness, with experiments showing it can handle up to 4.26 Tbps of bandwidth on a single low-end machine core without degrading system productivity.
Peer-assisted content distribution networks(CDNs) have emerged to improve performance and reduce deployment costs of traditional, infrastructure-based content delivery networks. This is done by employing peer-to-peer data transfers to supplement the resources of the network infrastructure. However, these hybrid systems are vulnerable to accounting attacks in which the peers, or caches, collude with clients in order to report that content was transferred when it was not. This is a particular issue in systems that incentivize cache participation, because malicious caches may collect rewards from the content publishers operating the CDN without doing any useful work. In this paper, we introduce CAPnet, the first technique that lets untrusted caches join a peer-assisted CDN while providing a bound on the effectiveness of accounting attacks. At its heart is a lightweight cache accountability puzzle that clients must solve before caches are given credit. This puzzle requires colocating the data a client has requested, so its solution confirms that the content (or at least an amount of data within a pre-configured bound) has actually been retrieved. We analyze the security and overhead of our scheme in realistic scenarios. The results show that a modest client machine using a single core can solve puzzles at a rate sufficient to simultaneously watch dozens of 1080p videos. The technique is designed to be even more scalable on the server side. In our experiments, one core of a single low-end machine is able to generate puzzles for 4.26 Tbps of bandwidth - enabling 870,000 clients to concurrently view the same 1080p video. This demonstrates that our scheme can ensure cache accountability without degrading system productivity.