Introduction
Understanding traffic behavior is an important part of network operations and management. A decade of research on traffic classification has provided various techniques to identify types of traffic information. As the Internet continuously evolves in scope and complexity, its traffic characteristics are also changing in terms of traffic composition and volume. Peer-to-peer (P2P) and multimedia traffic applications have rapidly grown in popularity, and their traffic occupies a great portion of the total Internet traffic volume these days. Kim et al. [1] have shown that P2P applications generate a substantial volume in enterprise networks. In 2008, a study by a Japanese Internet service provider (ISP) [2] observed that a significant portion of P2P traffic is recently being replaced by multimedia and web traffic. In par-ticular, a newer generation of P2P applications is incorporated with various obfuscation strategies, such as ephemeral port allocation and proprietary protocols, to avoid detection and filtering. A popular communication application like Skype eludes detection by payload encryption or plain-text ciphers [3]. The dynamic nature of Internet traffic adversely affects the accuracy of traffic classification and makes it a more challenging task.