Dr. David Eckhoff

I am a Principal Scientist and the Director of the MoVES Lab at TUMCREATE, Singapore. My research focuses on future transportation technologies, simulation, the smart city, and privacy.

David Eckhoff, "Analysis of Attack Vectors and Suitable Defense Mechanisms for Flow Monitors," Master's Thesis, Department of Computer Science, University of Erlangen-Nuremberg, June 2009. (Advisors: Tobias Limmer and Falko Dressler)

Abstract

Flow monitoring is an approach to efficiently manage and monitor large scale networks. A flow monitor can also be installed to cope with rising security risks and detect ongoing attacks or anomalies. However, these monitors can be attacked themselves which becomes critical if the security solution of the whole network relies on this device. To identify possible attack vectors we analyze aggregation modules within flow-based network monitoring tools, which usually make use of fast look-up methods to be able to quickly assign received packets to their corresponding flows. In software-based aggregators, hash tables are usually used for this task. If attackers are able to create collisions by exploiting the used hash function, the hash table degenerates to linked lists with worst-case look-up times of O(n) and greatly reduce the performance of the aggregation modules. In this thesis, we analyze the aggregation modules of software-based flow meters Vermont and nProbe. We evaluate the resilience strength of used hash functions by theoretical analysis and confirm the results by performing real attacks. Lastly we present a hash function which we believe has none of the weaknesses we have discovered. The second part of this thesis examines DoS attacks against monitored networks or the monitor itself. These attacks can lead to extensive memory usage and increased export volume at the monitor. In a worst-case scenario every attack packet is represented by a single flow. We analyze the effects of TCP DDoS attacks on a flow monitor and present two approaches to minimize the damage caused by such an attack. The first detects TCP SYN attacks via the SYN/FIN ratio, the second observes the amount of newly created flows within the hash table of the monitor to detect attacks and identifies victim and attacker through TCP packet symmetry.

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@phdthesis{eckhoff2009analysis,
    author = {Eckhoff, David},
    school = {University of Erlangen-Nuremberg},
    title = {{Analysis of Attack Vectors and Suitable Defense Mechanisms for Flow Monitors}},
    year = {2009},
    month = {June},
    type = {Master's Thesis},
    advisor = {Limmer, Tobias and Dressler, Falko},
    institution = {Department of Computer Science},
    location = {Erlangen, Germany},
   }
   
   

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