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An algorithm to identify the bottleneck nodes linking two component networks in a simple network of networks (NoN) configuration is proposed. The proposed bottleneck identification algorithm is based on applying a support vector machine on clustered packet delay measurements. This algorithm has the advantage that it requires almost no information about the topology of the underlying NoN. Simulation results show that this algorithm can provide very good detection performance when the component networks of the NoN are not too small in size, or when the connectivity between nodes within the component networks is not too sparse. 

One of the difficulties of implementing and analyzing algorithms that achieve information theoretic limits is adapting asymptotic results to the finite block-length regime. Results on secrecy for both regimes utilize Shannon entropy and mutual information as metrics for security. In this paper, we determine that Shannon entropy does not necessarily have equal utility for wireless authentication in finite block-length regimes with a focus on the fingerprint embedding framework. Then, we apply a new security performance metric to the framework that is linked to min-entropy rather than Shannon entropy and is similar to cheating probability used in the literature. The metric is based upon an adversary's ability to correctly guess the secret key over many observations using maximum likelihood decoding. We demonstrate the effect that system parameters such as the length of the key and the identification tag have on an adversary's ability to attack successfully. We find that if given a large key, it is better to use it all at once, than to use some and then renew the key with the remaining bits after a certain number of transmissions.