Amir Reza Ramtin
Abstract
We state and prove the square root scaling laws for the amount of traffic injected by a covert attacker into a network from a set of homes under the assumption that traffic descriptors follow a multivariate Gaussian distribution. We numerically evaluate the obtained result under realistic settings wherein traffic is collected from real users, leveraging detectors that exploit multiple features. Under such circumstances, we observe that phase transitions predicted by the model still hold.
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