5 research outputs found

    The Embedding Capacity of Information Flows Under Renewal Traffic

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    Given two independent point processes and a certain rule for matching points between them, what is the fraction of matched points over infinitely long streams? In many application contexts, e.g., secure networking, a meaningful matching rule is that of a maximum causal delay, and the problem is related to embedding a flow of packets in cover traffic such that no traffic analysis can detect it. We study the best undetectable embedding policy and the corresponding maximum flow rate ---that we call the embedding capacity--- under the assumption that the cover traffic can be modeled as arbitrary renewal processes. We find that computing the embedding capacity requires the inversion of very structured linear systems that, for a broad range of renewal models encountered in practice, admits a fully analytical expression in terms of the renewal function of the processes. Our main theoretical contribution is a simple closed form of such relationship. This result enables us to explore properties of the embedding capacity, obtaining closed-form solutions for selected distribution families and a suite of sufficient conditions on the capacity ordering. We evaluate our solution on real network traces, which shows a noticeable match for tight delay constraints. A gap between the predicted and the actual embedding capacities appears for looser constraints, and further investigation reveals that it is caused by inaccuracy of the renewal traffic model rather than of the solution itself.Comment: Sumbitted to IEEE Trans. on Information Theory on March 10, 201

    DDoS Attacks with Randomized Traffic Innovation: Botnet Identification Challenges and Strategies

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    Distributed Denial-of-Service (DDoS) attacks are usually launched through the botnetbotnet, an "army" of compromised nodes hidden in the network. Inferential tools for DDoS mitigation should accordingly enable an early and reliable discrimination of the normal users from the compromised ones. Unfortunately, the recent emergence of attacks performed at the application layer has multiplied the number of possibilities that a botnet can exploit to conceal its malicious activities. New challenges arise, which cannot be addressed by simply borrowing the tools that have been successfully applied so far to earlier DDoS paradigms. In this work, we offer basically three contributions: i)i) we introduce an abstract model for the aforementioned class of attacks, where the botnet emulates normal traffic by continually learning admissible patterns from the environment; ii)ii) we devise an inference algorithm that is shown to provide a consistent (i.e., converging to the true solution as time progresses) estimate of the botnet possibly hidden in the network; and iii)iii) we verify the validity of the proposed inferential strategy over realreal network traces.Comment: Submitted for publicatio

    Limits of Reliable Communication with Low Probability of Detection on AWGN Channels

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    We present a square root limit on the amount of information transmitted reliably and with low probability of detection (LPD) over additive white Gaussian noise (AWGN) channels. Specifically, if the transmitter has AWGN channels to an intended receiver and a warden, both with non-zero noise power, we prove that o(n)o(\sqrt{n}) bits can be sent from the transmitter to the receiver in nn channel uses while lower-bounding α+β≥1−ϵ\alpha+\beta\geq1-\epsilon for any ϵ>0\epsilon>0, where α\alpha and β\beta respectively denote the warden's probabilities of a false alarm when the sender is not transmitting and a missed detection when the sender is transmitting. Moreover, in most practical scenarios, a lower bound on the noise power on the channel between the transmitter and the warden is known and O(n)O(\sqrt{n}) bits can be sent in nn LPD channel uses. Conversely, attempting to transmit more than O(n)O(\sqrt{n}) bits either results in detection by the warden with probability one or a non-zero probability of decoding error at the receiver as n→∞n\rightarrow\infty.Comment: Major revision in v2. Context, esp. the relationship to steganography updated. Also, added discussion on secret key length. Results are unchanged from previous version. Minor revision in v3. Major revision in v4, Clarified derivations (adding appendix), also context, esp. relationship to previous work in communication updated. Results are unchanged from previous revision
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