4-th Ieee International Conference on Peer-to-peer Computing 100 Million Dht Replies

Crawling a DHT allows researchers to monitor the behaviour of peers, determine their geographic location, etc. However, it has always been an error-prone process as it is not feasible to capture a full snapshot of the Mainline DHT in a timely manner. Therefore, researchers have developed approximation methods which can run on subsets of the DHT and extrapolate those in order to reason on the size and structure of the complete DHT. However, in this paper we introduce a new method of collecting information on peers connected to a DHT. We exploit the caches present at bootstrap servers to collect information on peers which are currently connected. Originally added to the bootstrap servers in order to be able to withstand more than 20,000 requests for peers each second, we now use the same mechanism as peers bootstrapping into the DHT to discover more than 20 Million peers in less than 2 hours. Using the bootstrap servers, we discover more than twice as many peers as BitMon, which crawls a subset of the DHT and then extrapolates. Moreover, in contrast to related work which often require highly customized/tuned BitTorrent clients, our script consists of 90 lines of Python code and runs on a simple laptop.