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Dissecting Darknets: Measurement and Performance Analysis

Published:01 May 2014Publication History
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Abstract

BitTorrent (BT) plays an important role in Internet content distribution. Because public BTs suffer from the free-rider problem, Darknets are becoming increasingly popular, which use Sharing Ratio Enforcement to increase their efficiency. We crawled and traced 17 Darknets from September 2009 to February 2011, and obtained datasets about over 5 million torrents. We conducted a broad range of measurements, including traffic, sites, torrents, and users activities. We found that some of the features of Darknets are noticeably different from public BTs. The results of our study reflect both macroscopic and microscopic aspects of the overall ecosystem of BitTorrent Darknets.

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  1. Dissecting Darknets: Measurement and Performance Analysis

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      RuayShiung Chang

      If you are old enough, you probably remember Napster, a music downloading service using peer-to-peer (P2P) technology. Before Napster, file sharing, or any network service for that matter, used the client-server model, where a server is responsible for handling client requests. If there are many clients requesting services simultaneously, the server will be overloaded and unable to respond in time. On the contrary, in a P2P system, everyone in the network (a node) is both a client and a server. Every node has something that others want. Many communications between two nodes can take place at the same time, thus eliminating the server bottleneck. However, one critical thing remains to be done: determining who has something that somebody wants. Napster was a service for locating the data or resources that existed in a node. Therefore, when the data (for example, music in MP3 form) violated copyright law, Napster became an easy target for law enforcement bureaus. As a result, various techniques have been developed to distribute the data location information in the network itself. Still, law enforcement officials could infiltrate the P2P network and find all of the machines distributing the illegal material. To prevent such a scenario from happening, some P2P networks adopt a policy that requires users to register to use the P2P network, isolating it from nonregistered users. This is called a darknet. This paper tries to find out some statistical data from these darknets. Alas, the data dissected seemed to be too intuitive. For example, since becoming a user in a darknet requires an invitation and approval, users in a darknet feel safer exchanging copyrighted material. Therefore, they put the data online for a longer amount of time, making it readily available and reducing the downloading time. It would be interesting to know what types of content are exchanged most often in a darknet. What kind of people use darknets__?__ Is anonymity allowed and protected__?__ Online Computing Reviews Service

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      • Published in

        cover image ACM Transactions on Internet Technology
        ACM Transactions on Internet Technology  Volume 13, Issue 3
        May 2014
        97 pages
        ISSN:1533-5399
        EISSN:1557-6051
        DOI:10.1145/2630790
        • Editor:
        • Munindar P. Singh
        Issue’s Table of Contents

        Copyright © 2014 ACM

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 1 May 2014
        • Accepted: 1 February 2014
        • Revised: 1 January 2014
        • Received: 1 November 2012
        Published in toit Volume 13, Issue 3

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