6,973 research outputs found

    Stochastic Dynamic Cache Partitioning for Encrypted Content Delivery

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    In-network caching is an appealing solution to cope with the increasing bandwidth demand of video, audio and data transfer over the Internet. Nonetheless, an increasing share of content delivery services adopt encryption through HTTPS, which is not compatible with traditional ISP-managed approaches like transparent and proxy caching. This raises the need for solutions involving both Internet Service Providers (ISP) and Content Providers (CP): by design, the solution should preserve business-critical CP information (e.g., content popularity, user preferences) on the one hand, while allowing for a deeper integration of caches in the ISP architecture (e.g., in 5G femto-cells) on the other hand. In this paper we address this issue by considering a content-oblivious ISP-operated cache. The ISP allocates the cache storage to various content providers so as to maximize the bandwidth savings provided by the cache: the main novelty lies in the fact that, to protect business-critical information, ISPs only need to measure the aggregated miss rates of the individual CPs and do not need to be aware of the objects that are requested, as in classic caching. We propose a cache allocation algorithm based on a perturbed stochastic subgradient method, and prove that the algorithm converges close to the allocation that maximizes the overall cache hit rate. We use extensive simulations to validate the algorithm and to assess its convergence rate under stationary and non-stationary content popularity. Our results (i) testify the feasibility of content-oblivious caches and (ii) show that the proposed algorithm can achieve within 10\% from the global optimum in our evaluation

    Universally Composable Quantum Multi-Party Computation

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    The Universal Composability model (UC) by Canetti (FOCS 2001) allows for secure composition of arbitrary protocols. We present a quantum version of the UC model which enjoys the same compositionality guarantees. We prove that in this model statistically secure oblivious transfer protocols can be constructed from commitments. Furthermore, we show that every statistically classically UC secure protocol is also statistically quantum UC secure. Such implications are not known for other quantum security definitions. As a corollary, we get that quantum UC secure protocols for general multi-party computation can be constructed from commitments

    Compositional closure for Bayes Risk in probabilistic noninterference

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    We give a sequential model for noninterference security including probability (but not demonic choice), thus supporting reasoning about the likelihood that high-security values might be revealed by observations of low-security activity. Our novel methodological contribution is the definition of a refinement order and its use to compare security measures between specifications and (their supposed) implementations. This contrasts with the more common practice of evaluating the security of individual programs in isolation. The appropriateness of our model and order is supported by our showing that our refinement order is the greatest compositional relation --the compositional closure-- with respect to our semantics and an "elementary" order based on Bayes Risk --- a security measure already in widespread use. We also relate refinement to other measures such as Shannon Entropy. By applying the approach to a non-trivial example, the anonymous-majority Three-Judges protocol, we demonstrate by example that correctness arguments can be simplified by the sort of layered developments --through levels of increasing detail-- that are allowed and encouraged by compositional semantics

    On the integration of interest and power awareness in social-aware opportunistic forwarding algorithms

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    Social-aware Opportunistic forwarding algorithms are much needed in environments which lack network infrastructure or in those that are susceptible to frequent disruptions. However, most of these algorithms are oblivious to both the user’s interest in the forwarded content and the limited power resources of the available mobile nodes. This paper proposes PI-SOFA, a framework for integrating the awareness of both interest and power capability of a candidate node within the forwarding decision process. Furthermore, the framework adapts its forwarding decisions to the expected contact duration between message carriers and candidate nodes. The proposed framework is applied to three state-of-the-art social-aware opportunistic forwarding algorithms that target mobile opportunistic message delivery. A simulation-based performance evaluation demonstrates the improved effectiveness, efficiency, reduction of power consumption, and fair utilization of the proposed versions in comparison to those of the original algorithms. The results show more than 500% extra f-measure, mainly by disregarding uninterested nodes while focusing on the potentially interested ones. Moreover, power awareness preserves up to 8% power with 41% less cost to attain higher utilization fairness by focusing on power-capable interested nodes. Finally, this paper analyzes the proposed algorithms’ performance across various environments. These findings can benefit message delivery in opportunistic mobile networks
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