Collaborative Spam Filtering Using E-Mail Networks

Almost all of us have multiple cyberspace identities, and these cyberalter egos are networked together to form a vast cyberspace social network. This network is distinct from the world-wideweb (WWW), which is being queried and mined to the tune of billions of dollars everyday, and until recently, has gone largely unexplored. Empirically, the cyberspace social networks have been found to possess many of the same complex features that characterize its real counterparts, including scalefree degree distributions, low diameter, and extensive connectivity. We show that these topological features make the latent networks particularly suitable for explorations and management via localonly messaging protocols. Cyberalter egos can communicate via their direct links (i.e., using only their own address books) and set up a highly decentralized and scalable message passing network that can allow large-scale sharing of information and data. As one particular example of such collaborative systems, we provide a design of a spam filtering system, and our large-scale simulations show that the system achieves a spam detection rate close to 100%, while the false positive rate is kept around zero. This system of letting cyberalter egos network among themselves has several advantages over other recent proposals for collaborative spam filtering: (i) It uses an already existing network, created by the same social dynamics that govern our daily lives, and no dedicated peerto-peer (P2P) systems or centralized server-based systems need be constructed; (ii) It utilizes a percolation search algorithm (which can be viewed as mimicking how rumor is spread in a social network) that makes the query-generated traffic scalable; (iii) The network has a built in trust system (just as in social networks) that can be used to thwart malicious attacks; and (iv) It can be implemented right now as a plugin to popular email programs, such as MS Outlook, Eudora, and Sendmail.