29,357 research outputs found

    Cross-Layer Peer-to-Peer Track Identification and Optimization Based on Active Networking

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    P2P applications appear to emerge as ultimate killer applications due to their ability to construct highly dynamic overlay topologies with rapidly-varying and unpredictable traffic dynamics, which can constitute a serious challenge even for significantly over-provisioned IP networks. As a result, ISPs are facing new, severe network management problems that are not guaranteed to be addressed by statically deployed network engineering mechanisms. As a first step to a more complete solution to these problems, this paper proposes a P2P measurement, identification and optimisation architecture, designed to cope with the dynamicity and unpredictability of existing, well-known and future, unknown P2P systems. The purpose of this architecture is to provide to the ISPs an effective and scalable approach to control and optimise the traffic produced by P2P applications in their networks. This can be achieved through a combination of different application and network-level programmable techniques, leading to a crosslayer identification and optimisation process. These techniques can be applied using Active Networking platforms, which are able to quickly and easily deploy architectural components on demand. This flexibility of the optimisation architecture is essential to address the rapid development of new P2P protocols and the variation of known protocols

    Unified Description for Network Information Hiding Methods

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    Until now hiding methods in network steganography have been described in arbitrary ways, making them difficult to compare. For instance, some publications describe classical channel characteristics, such as robustness and bandwidth, while others describe the embedding of hidden information. We introduce the first unified description of hiding methods in network steganography. Our description method is based on a comprehensive analysis of the existing publications in the domain. When our description method is applied by the research community, future publications will be easier to categorize, compare and extend. Our method can also serve as a basis to evaluate the novelty of hiding methods proposed in the future.Comment: 24 pages, 7 figures, 1 table; currently under revie

    Repository Replication Using NNTP and SMTP

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    We present the results of a feasibility study using shared, existing, network-accessible infrastructure for repository replication. We investigate how dissemination of repository contents can be ``piggybacked'' on top of existing email and Usenet traffic. Long-term persistence of the replicated repository may be achieved thanks to current policies and procedures which ensure that mail messages and news posts are retrievable for evidentiary and other legal purposes for many years after the creation date. While the preservation issues of migration and emulation are not addressed with this approach, it does provide a simple method of refreshing content with unknown partners.Comment: This revised version has 24 figures and a more detailed discussion of the experiments conducted by u

    CHASING THE UNKNOWN: A PREDICTIVE MODEL TO DEMYSTIFY BGP COMMUNITY SEMANTICS

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    The Border Gateway Protocol (BGP) specifies an optional communities attribute for traffic engineering, route manipulation, remotely-triggered blackholing, and other services. However, communities have neither unifying semantics nor cryptographic protections and often propagate much farther than intended. Consequently, Autonomous System (AS) operators are free to define their own community values. This research is a proof-of-concept for a machine learning approach to prediction of community semantics; it attempts a quantitative measurement of semantic predictability between different AS semantic schemata. Ground-truth community semantics data were collated and manually labeled according to a unified taxonomy of community services. Various classification algorithms, including a feed-forward Multi-Layer Perceptron and a Random Forest, were used as the estimator for a One-vs-All multi-class model and trained according to a feature set engineered from this data. The best model's performance on the test set indicates as much as 89.15% of these semantics can be accurately predicted according to a proposed standard taxonomy of community services. This model was additionally applied to historical BGP data from various route collectors to estimate the taxonomic distribution of communities transiting the control plane.http://archive.org/details/chasingtheunknow1094566047Outstanding ThesisCivilian, CyberCorps - Scholarship For ServiceApproved for public release. distribution is unlimite
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