Biblio

Identifying services constituting traffic from given IP network flows is essential to various applications, such as the management of quality of service (QoS) and the prevention of security issues. Typical methods for achieving this objective include identifications based on IP addresses and port numbers. However, such methods are not sufficiently accurate and require improvement. Deep Packet Inspection (DPI) is one of the most promising methods for improving the accuracy of identification. In addition, many current IP flows are encrypted using Transport Layer Security (TLS). Hence, it is necessary for identification methods to analyze flows encrypted by TLS. For that reason, a service identification method based on DPI and n-gram that focuses only on the non-encrypted parts in the TLS session establishment was proposed. However, there is room for improvement in identification accuracy because this method analyzes all the non-encrypted parts including Random Values without protocol analyses. In this paper, we propose a method for identifying the service from given IP flows based on analysis of Server Name Indication (SNI). The proposed method clusters flow according to the value of SNI and identify services from the occurrences of all clusters. Our evaluations, which involve identifications of services on Google and Yahoo sites, demonstrate that the proposed method can identify services more accurately than the existing method.

Large scale applications in data centers are composed of computers connected with a network. Traditional network switches cannot be flexibly controlled. Then, application developer cannot optimize network elements' behavior for improving application performance. On the other hand, Deeply Programmable Network (DPN) switches can completely analyze packet payloads and be profoundly programmed. In this paper, we focus on processing a part of application functions in network elements for improving application performance based on Deep Packet Inspection (DPI), i.e. analyzing packet payload, using DPN switches. We assume some applications as targets and implement some of functions of applications in network switches. We then present the comparison of performances with and without out method, and show that our method can significantly increase application performance.