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FlowRank: ranking NetFlow records

FlowRank: ranking NetFlow records,10.1145/1815396.1815508,Shaonan Wang,Radu State,Mohamed Ourdane,Thomas Engel

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FlowRank: ranking NetFlow records   (Citations: 2)
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This paper describes a new approach to identify relevant flow records in large scale flow dataset. We propose a method that leverages the well known page rank algorithm in order to extract the most relevant flows. We introduce a dependency relation that uses a simple and efficient causal relationship. The strength of this dependency is determined by time related information. We have tested our method on datasets coming from our campus network.
Conference: International Conference on Wireless Communications and Mobile Computing - IWCMC , pp. 484-488, 2010
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    • ...Our previous work has leveraged link analysis algorithms on flow dependency graphs [35,36] and host dependency graphs [37] for tracing the root cause flow records corresponding to the malicious traffic...
    • ...Flow dependency graphs [35,36] do not consider hosts as nodes but flows as nodes and try to build causal connections between them based on timing analysis...

    Jérôme François, et al. BotTrack: Tracking Botnets Using NetFlow and PageRank

    • ...In our previous work [26], [25], we studied the dependencies between IP flows instead of between hosts...
    • ...We have done previous work on link analysis techniques for network management in [25], [26] where we proposed a dependency model that directly used the IP flow records as an underlying topology...

    Shaonan Wang, et al. RiskRank: Security risk ranking for IP flow records

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