Towards identification of operating systems from the internet traffic: IPFIX monitoring with fingerprinting and clustering

This paper deals with identification of operating systems (OSs) from the Internet traffic. Every packet injected on the network carries a specific information in its packet header that reflects the initial settings of a host's operating system. The set of such features forms a fingerprint. The OS fingerprint usually includes an initial TTL time, a TCP initial window time, a set of specific TCP options, and other values obtained from IP and TCP headers. Identification of OSs can be useful for monitoring a traffic on a local network and also for security purposes. In our paper we focus on the passive fingerprinting using TCP SYN packets that is incorporated to a IPFIX probe. Our tool enhances standard IPFIX records by additional information about OSs. Then, it sends the records to an IPFIX collector where network statistics are stored and presented to the network administrator. If identification is not successful, a further HTTP header check is employed and the fingerprinting database in the probe is updated. Our fingerprinting technique can be extended using cluster analysis as presented in this paper. As we show the clustering adds flexibility and dynamics to the fingerprinting. We also discuss the impact of IPv6 protocol on the passive fingerprinting.