Abstract. The identification of application flows is a critical task in order to manage bandwidth requirements of different kind of services (i.e. VOIP, Video, ERP). As network security functions spread, an increasing amount of traffic is natively encrypted due to privacy issues (e.g. VPN). This makes ineffective current traffic classification systems based on ports and payload inspection, e.g. even powerful Deep Packet Inspection is useless to classify application flow carried inside SSH sessions. We have developed a real time traffic classification method based on cluster analysis to identify SSH flows from statistical behavior of IP traffic parameters, such as length, arrival times and direction of packets. In this paper we describe our approach and relevant obtained results. We achieve detection rate up to 99.5 % in classifying SSH flows and accuracy up to 99.88 % for application flows carried within those flows, such as SCP, SFTP and HTTP over SSH.

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The challenge to address in multi-firewall and security gateway environment is to implement conflict-free policies, necessary to avoid security inconsistency, and to optimize, at the same time, performances in term of average filtering time, in order to make firewalls stronger against DoS and DDoS attacks. Additionally the approach should be real time, based on the characteristics of network traffic. Our work defines an algorithm to find conflict free optimized device rule sets in real time, by relying on information gathered from traffic analysis. We show results obtained from our test environment demonstrating for computational power savings up to 24% with fully conflict free device policies.

Security rules management in firewall and security gateway is a hard and error prone task as administrators must correctly implement and update a large amount of policies especially when rapid changing occurs due to new security needs. The challenge to address in multi-firewall and security gateway environment is to implement conflict-free policies, necessary to avoid security inconsistency, and to optimize, at the same time, performances in term of average filtering time, in order to make firewalls stronger against DoS and DDoS attacks. Additionally the approach should be real time, based on the characteristics of network traffic. There is a vast amount of literature on security policy conflict detection and resolution and on device rule set shaping to improve policy implementation performance. Our work defines an algorithm to find conflict free optimized device rule sets in real time, by relying on information gathered from traffic analysis. We show results obtained from our test environment confirming that operational costs of devices could be improved based on traffic analysis via log files of the security device. We demonstrate computational power savings up to 24% with fully conflict free device policies. ©2008 IEEE

Packet filtering and processing rules management in firewalls and security gateways has become commonplace in increasingly complex networks. On one side there is a need to maintain the logic of high level policies, which requires administrators to implement and update a large amount of filtering rules while keeping them conflict-free, that is, avoiding security inconsistencies. On the other side, traffic adaptive optimization of large rule lists is useful for general purpose computers used as filtering devices, without specific designed hardware, to face growing link speeds and to harden filtering devices against DoS and DDoS attacks. Our work joins the two issues in an innovative way and defines a traffic adaptive algorithm to find conflict-free optimized rule sets, by relying on information gathered with traffic logs. The proposed approach suits current technology architectures and exploits available features, like traffic log databases, to minimize the impact of ACO development on the packet filtering devices. We demonstrate the benefit entailed by the proposed algorithm through measurements on a test bed made up of real-life, commercial packet filtering devices.