Approximate Object Location and Spam Filtering on Peer-to-Peer Systems

摘要

Recent work in P2P overlay networks allow for decentralized object location and routing (DOLR) across networks based on unique IDs. In this paper, we propose an extension to DOLR systems to publish objects using generic feature vectors instead of content-hashed GUIDs, which enables the systems to locate similar objects. We discuss the design of a distributed text similarity engine, named Approximate Text Addressing (ATA), built on top of this extension that locates objects by their text descriptions. We then outline the design and implementation of a motivating application on ATA, a decentralized spam-filtering service. We evaluate this system with 30,000 real spam email messages and 10,000 non-spam messages, and find a spam identification ratio of over 97% with zero false positives.