Detecting illegal file sharing in Peer-to-Peer networks using fuzzy queries

The advent of Unstructured Peer-to-Peer (P2P) networks enables large amounts of content to be distributed over Internet. However, billions of dollars are lost every year as a consequence of illegal file sharing or piracy. The main focus towards detecting this has been in educating the public about legal file sharing alternatives instead of developing systems and architectures that define protocols, and mechanism. Within our knowledge, there is a lack of specialized protocols, and mechanisms that can detect possible sources of illegal file sharing in a P2P network and do not increment the query traffic. Much of the P2P query traffic is caused by the keyword search method enabled in P2P networks; a typical P2P network uses query broadcast to enable keyword search and are not able to express impreciseness. These protocols and mechanisms can be reinforced by the use of fuzzy logic. We propose an architecture that integrates fuzzy queries and an inference process with a P2P protocol called Localized Fuzzy Search Protocol (LFSP). The LFSP decreases P2P traffic and enables the discovering possible sources of illegal file sharing by querying directly the P2P sources. Finally, our architecture can be used by organizations wishing to detect possible sources of illegal file sharing and that are willing to take the corresponding actions.