NCShield: securing decentralized, matrix factorization-based network coordinate systems

Abstract

While network coordinate (NC) systems provide scalable Internet distance estimation service and are useful for various Internet applications, decentralized, matrix factorization-based NC (MFNC) systems have received particular attention recently. They can serve large-scale distributed applications (as opposed to centralized NC systems) and do not need to assume triangle inequality (as opposed to Euclidean-based NC systems). However, because of their decentralized nature, MFNC systems are vulnerable to various malicious attacks. In this paper, we provide the first study on attacks toward MFNC systems, and propose a decentralized trust and reputation approach, called NCShield, to counter such attacks. Different from previous approaches, our approach is able to distinguish between legitimate distance variations and malicious distance alterations. Using four representative data sets from the Internet, we show that NCShield can defend against attacks with high accuracy. For example, when selecting node pairs with a shorter distance than a predefined threshold in an online game scenario, even if 30% nodes are malicious, NCShield can reduce the false positive rate from 45.5% to 3.7%.