Juan A. Elices

Juan A. Elices, Fernando Perez-Gonzalez

Deciding that two network flows are essentially the same is an important problem in intrusion detection and in tracing anonymous connections. A stepping stone or an anonymity network may try to prevent flow correlation by adding chaff traffic, splitting the flow in several subflows or adding random delays. A well-known attack for these types of systems is active watermarking. However, active watermarking systems can be detected and an attacker can modify the flow in such a way that the watermark is removed and can no longer be decoded. This leads to the two basic features of our scheme: a highlyoptimized algorithm that achieves very good performance and a passive analysis that is undetectable. We propose a new passive analysis technique where detection is based on Neyman-Pearson lemma. We correlate the inter-packet delays (IPDs) from both flows. Then, we derive a modification to deal with stronger adversary models that add chaff traffic, split the flows or add random delays. We empirically validate the detectors with a simulator. Afterwards, we create a watermarkbased version of our scheme to study the trade-off between performance and detectability. Then, we compare the results with other state-of-the-art traffic watermarking schemes in several scenarios concluding that our scheme outperforms the rest. Finally, we present results using an implementation of our method on live networks, showing that the conclusions can be extended to real-world scenarios. Our scheme needs only tens of packets under normal network interference and a few hundreds of packets when a number of countermeasures are taken.

Juan A. Elices, Fernando Perez-Gonzalez

Linking two network flows that have the same source is essential in intrusion detection or in tracing anonymous connections. To improve the performance of this process, the flow can be modified (fingerprinted) to make it more distinguishable. However, an adversary located in the middle can modify the flow to impair the correlation by delaying the packets or introducing dummy traffic. We introduce a game-theoretic framework for this problem, that is used to derive the Nash Equilibrium. As obtaining the optimal adversary delays distribution is intractable, some approximations are done. We study the concrete example where these delays follow a truncated Gaussian distribution. We also compare the optimal strategies with other fingerprinting schemes. The results are useful for understanding the limits of flow correlation based on packet timings under an active attacker.

Juan A. Elices, Fernando Perez-Gonzalez

Deciding that two network flows are essentially the same is an important problem in intrusion detection or in tracing anonymous connections. A stepping stone or an anonymity network may try to prevent flow correlation by delaying the packets, introducing chaff traffic, or even splitting the flow in several subflows. We introduce a game-theoretic framework for this problem. The framework is used to derive the Nash equilibrium under two different adversary models: the first one, when the adversary is limited to delaying packets, and the second, when the adversary also adds dummy packets and removes packets from the flow. As the optimal decoder is not computationally feasible, we restrict the possible decoder to one that estimates and compensates the attack. Our analysis can be used for understanding the limits of flow correlation based on packet timings under an active attacker.