The Experts below are selected from a list of 813 Experts worldwide ranked by ideXlab platform
Michel Clement - One of the best experts on this subject based on the ideXlab platform.
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Fernsehen im Zeitalter von Networked Personal Video Recordern
Schmalenbachs Zeitschrift für betriebswirtschaftliche Forschung, 2004Co-Authors: Michel ClementAbstract:A personal video recorder (PVR) is a video recorder with a hard drive or a PC with an integrated TV tuner card. Instead of recording the movies on an analogue tape, they record content digitally on the PVR’s hard drive. PVRs can be connected to the Internet, allowing users to (illegally) massively distribute recorded content online using for example peer-to-peer networks like Kazaa. The PVR technology enables new services, which influence the traditional business models of broadcasters (free and pay TV). On the one hand shows containing commercials are recorded and stored digitally on a user’s hard drive, which allows easy skipping of ads. Some PVRs even automatically skip ads while playing the recording. On the other hand pay TV content is widely available for free on illegal channels like Kazaa reducing the uniqueness of pay TV offerings. This article discusses the risks arising with increasing diffusion of PVRs. Depending on the chosen formats the risks for the business models of free and pay TV stations are presented. The article finally provides strategic implications for TV stations facing the competition of PVRs.
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Fernsehen im Zeitalter von Networked Personal Video Recordern
Schmalenbachs Zeitschrift für betriebswirtschaftliche Forschung, 2004Co-Authors: Michel ClementAbstract:A personal video recorder (PVR) is a video recorder with a hard drive or a PC with an integrated TV tuner card. Instead of recording the movies on an analogue tape, they record content digitally on the PVR’s hard drive. PVRs can be connected to the Internet, allowing users to (illegally) massively distribute recorded content online using for example peer-to-peer networks like Kazaa.
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Digital Rights Management - Lessons from Content-for-Free Distribution Channels
Lecture Notes in Computer Science, 2003Co-Authors: Michel ClementAbstract:The most challenging task facing McGlade is licensing content for MusicNet, but the content he is looking for is already digitized, compressed, labeled, and widely published on the Internet. Peer-to-peer networks like Kazaa or iMesh virtually offer all content users desire. The only problem is that right owners did not license the content to them and users are acting illegal, if they offer content – and in some countries, when they download it.
John Zahorjan - One of the best experts on this subject based on the ideXlab platform.
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ABSTRACT Measurement, Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload
2008Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so,we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First,we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second,we develop a model of multimedia workloads that lets us isolate,vary,and explore the impact of key system parameters. Our model,which we parameterize with statistics from our trace,lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third,we explore the potential impact of localityawareness in Kazaa
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measurement modeling and analysis of a peer to peer file sharing workload
Symposium on Operating Systems Principles, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.
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SOSP - Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
Proceedings of the nineteenth ACM symposium on Operating systems principles - SOSP '03, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.
Hari Balakrishnan - One of the best experts on this subject based on the ideXlab platform.
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Malware Prevalence in the Kazaa File-Sharing Network Seungwon Shin ETRI
2014Co-Authors: Daejeon Korea, Jaeyeon Jung, Hari BalakrishnanAbstract:In recent years, more than 200 viruses have been reported to use a peer-to-peer (P2P) file-sharing network as a propagation vector. Disguised as files that are frequently exchanged over P2P networks, these malicious programs infect the user’s host if downloaded and opened, leaving their copies in the user’s sharing folder for further propagation. Using a light-weight crawler built for the Kazaa file-sharing network, we study the prevalence of malware in this popular P2P network, the malware’s propagation behavior in the P2P network environment and the characteristics of infected hosts. We gathered information about more than 500,000 files returned by the Kazaa network in response to 24 common query strings. With 364 signatures of known malicious programs, we found that over 15 % of the crawled files were infected by 52 different viruses. Many of the malicious programs that we find active in the Kazaa P2P network open a backdoor through which an attacker can remotely control the compromised machine, send spam, or steal a user’s confidential information. The assertion that these hosts were used to send spam was supported by the fact that over 70 % of infected hosts were listed on DNS-based spam black-lists. Our measurement method is efficient: it enables us to investigate more than 30,000 files in an hour, identifying infected hosts without directly accessing their file system
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Malware Prevalence in the Kazaa File-Sharing Network ABSTRACT Seungwon Shin ETRI
2008Co-Authors: Daejeon Korea, Jaeyeon Jung, Hari BalakrishnanAbstract:In recent years, more than 200 viruses have been reported to use a peer-to-peer (P2P) file-sharing network as a propagation vector. Disguised as files that are frequently exchanged over P2P networks, these malicious programs infect the user’s host if downloaded and opened, leaving their copies in the user’s sharing folder for further propagation. Using a light-weight crawler built for the Kazaa file-sharing network, we study the prevalence of malware in this popular P2P network, the malware’s propagation behavior in the P2P network environment and the characteristics of infected hosts. We gathered information about more than 500,000 files returned by the Kazaa network in response to 24 common query strings. With 364 signatures of known malicious programs, we found that over 15 % of the crawled files were infected by 52 different viruses. Many of the malicious programs that we find active in the Kazaa P2P network open a backdoor through which an attacker can remotely control the compromised machine, send spam, or steal a user’s confidential information. The assertion that these hosts were used to send spam was supported by the fact that over 70 % of infected hosts were listed on DNS-based spam black-lists. Our measurement method is efficient: it enables us to investigate more than 30,000 files in an hour, identifying infected hosts without directly accessing their file system
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Malware prevalence in the Kazaa file-sharing network
2007Co-Authors: Seungwon Shin, Jaeyeon Jung, Hari BalakrishnanAbstract:In recent years, more than 200 viruses have been reported to use a peer-to-peer (P2P) file-sharing network as a propagation vector. Disguised as files that are frequently exchanged over P2P networks, these malicious programs infect the user's host if downloaded and opened, leaving their copies in the user's sharing folder for further propagation. Using a light-weight crawler built for the Kazaa file-sharing network, we study the prevalence of malware in this popular P2P network, the malware's propagation behavior in the P2P network environment and the characteristics of infected hosts. We gathered information about more than 500,000 files returned by the Kazaa network in response to 24 common query strings. With 364 signatures of known malicious programs, we found that over 15% of the crawled files were infected by 52 different viruses. Many of the malicious programs that we find active in the Kazaa P2P network open a backdoor through which an attacker can remotely control the compromised machine, send spam, or steal a user's confidential information. The assertion that these hosts were used to send spam was supported by the fact that over 70% of infected hosts were listed on DNS-based spam black-lists. Our measurement method is efficient: it enables us to investigate more than 30,000 files in an hour, identifying infected hosts without directly accessing their file system.
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Internet Measurement Conference - Malware prevalence in the Kazaa file-sharing network
Proceedings of the 6th ACM SIGCOMM on Internet measurement - IMC '06, 2006Co-Authors: Seungwon Shin, Jaeyeon Jung, Hari BalakrishnanAbstract:In recent years, more than 200 viruses have been reported to use a peer-to-peer (P2P) file-sharing network as a propagation vector. Disguised as files that are frequently exchanged over P2P networks, these malicious programs infect the user's host if downloaded and opened, leaving their copies in the user's sharing folder for further propagation. Using a light-weight crawler built for the Kazaa file-sharing network, we study the prevalence of malware in this popular P2P network, the malware's propagation behavior in the P2P network environment and the characteristics of infected hosts. We gathered information about more than 500,000 files returned by the Kazaa network in response to 24 common query strings. With 364 signatures of known malicious programs, we found that over 15% of the crawled files were infected by 52 different viruses. Many of the malicious programs that we find active in the Kazaa P2P network open a backdoor through which an attacker can remotely control the compromised machine, send spam, or steal a user's confidential information. The assertion that these hosts were used to send spam was supported by the fact that over 70% of infected hosts were listed on DNS-based spam black-lists. Our measurement method is efficient: it enables us to investigate more than 30,000 files in an hour, identifying infected hosts without directly accessing their file system.
Krishna P Gummadi - One of the best experts on this subject based on the ideXlab platform.
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ABSTRACT Measurement, Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload
2008Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so,we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First,we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second,we develop a model of multimedia workloads that lets us isolate,vary,and explore the impact of key system parameters. Our model,which we parameterize with statistics from our trace,lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third,we explore the potential impact of localityawareness in Kazaa
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measurement modeling and analysis of a peer to peer file sharing workload
Symposium on Operating Systems Principles, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.
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SOSP - Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
Proceedings of the nineteenth ACM symposium on Operating systems principles - SOSP '03, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.
Henry M Levy - One of the best experts on this subject based on the ideXlab platform.
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ABSTRACT Measurement, Modeling, and Analysis of a Peer-to-Peer File-Sharing Workload
2008Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so,we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First,we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second,we develop a model of multimedia workloads that lets us isolate,vary,and explore the impact of key system parameters. Our model,which we parameterize with statistics from our trace,lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third,we explore the potential impact of localityawareness in Kazaa
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Measurement and analysis of internet content delivery systems
2004Co-Authors: Stefan Saroiu, Steven D Gribble, Henry M LevyAbstract:In recent years, the Internet has experienced an enormous increase in the use of specialized content delivery systems, such as peer-to-peer file-sharing systems (e.g., Kazaa, Gnutella, or Napster) and content delivery networks (e.g., Akamai). The sudden popularity of these systems has resulted in a flurry of research activity into novel peer-to-peer system designs. Because these systems: (1) are fully distributed, without any infrastructure that can be directly measured, (2) have novel distributed designs requiring new crawling techniques, and (3) use proprietary protocols, surprisingly little is known about the performance, behavior, and workloads of such systems in practice. Accordingly, much of the research into peer-to-peer networking is uninformed by the realities of deployed systems. This dissertation remedies this situation. We examine content delivery from the point of view of four content delivery systems: HTTP Web traffic, the Akamai content delivery network, and the Kazaa and Gnutella peer-to-peer file sharing networks. Our results (1) quantify the rapidly increasing importance of new content delivery systems, particularly peer-to-peer networks, and (2) characterize peer-to-peer systems both from an infrastructure and workload perspective. Overall, these results provide a new understanding of the behavior of the modern Internet and present a strong basis for the design of newer content delivery systems.
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measurement modeling and analysis of a peer to peer file sharing workload
Symposium on Operating Systems Principles, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.
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SOSP - Measurement, modeling, and analysis of a peer-to-peer file-sharing workload
Proceedings of the nineteenth ACM symposium on Operating systems principles - SOSP '03, 2003Co-Authors: Krishna P Gummadi, Richard J Dunn, Stefan Saroiu, Steven D Gribble, Henry M Levy, John ZahorjanAbstract:Peer-to-peer (P2P) file sharing accounts for an astonishing volume of current Internet traffic. This paper probes deeply into modern P2P file sharing systems and the forces that drive them. By doing so, we seek to increase our understanding of P2P file sharing workloads and their implications for future multimedia workloads. Our research uses a three-tiered approach. First, we analyze a 200-day trace of over 20 terabytes of Kazaa P2P traffic collected at the University of Washington. Second, we develop a model of multimedia workloads that lets us isolate, vary, and explore the impact of key system parameters. Our model, which we parameterize with statistics from our trace, lets us confirm various hypotheses about file-sharing behavior observed in the trace. Third, we explore the potential impact of locality-awareness in Kazaa.Our results reveal dramatic differences between P2P file sharing and Web traffic. For example, we show how the immutability of Kazaa's multimedia objects leads clients to fetch objects at most once; in contrast, a World-Wide Web client may fetch a popular page (e.g., CNN or Google) thousands of times. Moreover, we demonstrate that: (1) this "fetch-at-most-once" behavior causes the Kazaa popularity distribution to deviate substantially from Zipf curves we see for the Web, and (2) this deviation has significant implications for the performance of multimedia file-sharing systems. Unlike the Web, whose workload is driven by document change, we demonstrate that clients' fetch-at-most-once behavior, the creation of new objects, and the addition of new clients to the system are the primary forces that drive multimedia workloads such as Kazaa. We also show that there is substantial untapped locality in the Kazaa workload. Finally, we quantify the potential bandwidth savings that locality-aware P2P file-sharing architectures would achieve.