Unsupervised and nonparametric detection of information flows
Signal Processing
Detecting co-residency with active traffic analysis techniques
Proceedings of the 2012 ACM Workshop on Cloud computing security workshop
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We present an efficient and robust stepping-stone detection scheme based on succinct packet-timing sketches of network flows. The proposed scheme employs an online algorithm to continuously maintain short sketches of flows from a stream of captured packets at the network boundary. These sketches are then used to identify pairs of network flows with similar packet-timing characteristics, which indicates potential stepping-stones. Succinct flow sketches enable the proposed scheme to compare a given pair of flows in constant time. In addition, flow sketches identify pairs of correlated flows from a given list of flows in sub-quadratic time, thereby allowing a more scalable solution as compared to known schemes. Finally, the proposed scheme is resistant to random delays and chaff, which are often employed by attackers to evade detection. To explore its efficacy, we mathematically analyze the robustness properties of the proposed flow sketch. We also experimentally measure the detection performance of the proposed scheme.