標題: Hardware Design for Statistical Network Traffic Classifiers
作者: Lu, Chun-Nan
Lai, Yuan-Cheng
Huang, Chun-Ying
Lin, Ying-Dar
資訊工程學系
Department of Computer Science
關鍵字: traffic classification;packet size;message size distribution;sequence;hardware classifier
公開日期: 1-Jan-2016
摘要: Signature matching is commonly used in network traffic classification and can provide accurate and efficient results. However, it requires constant updates of signatures and can't be applied to encrypted traffic. Statistical behavior-based approaches can avoid the drawback of payload encryption. However, the computational complexity of related statistical features may prevent them being deployed in systems that are expected to respond in limited time. In this work, we combine the advantages of statistics-based classification approaches and hardware design techniques to develop a balanced classifier that can provide timely responses to. Two statistics-based solutions, a message size distribution classifier (MSDC) and a message size sequence classifier (MSSC) which depend on classification accuracy and real timeliness arc proposed. The former aims to identify network flows in an accurate but not-so-fast manner, while the latter aims to provide a lightweight and real-time solution. Simulations showed that MSSC contributed 77.4% and MSDC contributed 22.6% of decision rounds. Furthermore, our design can achieve an accuracy of more than 94% while achieving a throughput of 80 Gbps.
URI: http://hdl.handle.net/11536/146814
期刊: 2016 2ND IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC)
起始頁: 2425
結束頁: 2429
Appears in Collections:Conferences Paper