The Experts below are selected from a list of 72954 Experts worldwide ranked by ideXlab platform
Antonio Nucci - One of the best experts on this subject based on the ideXlab platform.
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sip based voip Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
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MineNet - SIP-based VoIP Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data - MineNet '07, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
Zhi-li Zhang - One of the best experts on this subject based on the ideXlab platform.
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Internet Traffic Behavior Profiling for Network Security Monitoring
IEEE/ACM Transactions on Networking, 2008Co-Authors: Kuai Xu, Zhi-li Zhang, Supratik BhattacharyyaAbstract:Recent spates of cyber-attacks and frequent emergence of applications affecting Internet Traffic dynamics have made it imperative to develop effective techniques that can extract, and make sense of, significant communication patterns from Internet Traffic data for use in network operations and security management. In this paper, we present a general methodology for building comprehensive Behavior profiles of Internet backbone Traffic in terms of communication patterns of end-hosts and services. Relying on data mining and entropy-based techniques, the methodology consists of significant cluster extraction, automatic Behavior classification and structural modeling for in-depth interpretive analyses. We validate the methodology using data sets from the core of the Internet.
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sip based voip Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
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MineNet - SIP-based VoIP Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data - MineNet '07, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
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Profiling internet backbone Traffic: Behavior models and applications
2005Co-Authors: Kuai Xu, Zhi-li Zhang, Supratik BhattacharyyaAbstract:Recent spates of cyber-attacks and frequent emergence of applications affecting Internet Traffic dynamics have made it imperative to develop effective techniques that can extract, and make sense of, significant communication patterns from Internet Traffic data for use in network operations and security management. In this paper, we present a general methodology for building comprehensive Behavior profiles of Internet backbone Traffic in terms of communication patterns of end-hosts and services. Relying on data mining and information-theoretic techniques, the methodology consists of significant cluster extraction, automatic Behavior classification and structural modeling for in-depth interpretive analyses. We validate the methodology using data sets from the core of the Internet. The results demonstrate that it indeed can identify common Traffic profiles as well as anomalous Behavior patterns that are of interest to network operators and security analysts.
Liu Qiang - One of the best experts on this subject based on the ideXlab platform.
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DDoS Detection System Based on Traffic Behavior
Computer Engineering, 2011Co-Authors: Liu QiangAbstract:Because many traditional detection algorithms can not real time inspect the attack source and the victim,based on single-user Traffic Behavioral analysis,this paper presents a real-time DDoS flooding attack detection and prevention system.Based on the time synchronization of TCP and UDP protocol Behavior,through periodically detecting every single IP user's sending and receiving Traffic and judging whether its Traffic Behaviors meet the synchronization or not.This system can effectively recognize attackers,victims and normal users,and real time filter attackers' Traffic and forward normal users' packets.Experimental results show that the system can make a real-time detection for DDoS flooding attacks and determine the attacker at the early attacking stage,and the defense effect is obvious.
Hun Jeong Kang - One of the best experts on this subject based on the ideXlab platform.
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sip based voip Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
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MineNet - SIP-based VoIP Traffic Behavior profiling and its applications
Proceedings of the 3rd annual ACM workshop on Mining network data - MineNet '07, 2007Co-Authors: Hun Jeong Kang, Zhi-li Zhang, Supranamaya Ranjan, Antonio NucciAbstract:With the widespread adoption of SIP-based VoIP, understanding the characteristics of SIP Traffic Behavior is critical to problem diagnosis and security protection of IP Telephony. In this paper, we propose a general methodology for profiling SIP-based VoIP Traffic Behavior at multiple levels: SIP server host, server entity and individual user levels. Using SIP Traffic traces captured in a production VoIP service, we illustrate the characteristics of SIP-based VoIP Traffic Behavior in an operational network and demonstrate the effectiveness of our general profiling methodology. In particular, we show how our profiling methodology can help identify performance anomalies through a case study.
Baisheng Zhang - One of the best experts on this subject based on the ideXlab platform.
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APPT - Measurement of high-speed IP Traffic Behavior based on routers
Lecture Notes in Computer Science, 1Co-Authors: Junpeng Mao, Julong Lan, Lian Guan, Baisheng ZhangAbstract:IP Traffic Behavior is becoming increasingly complicated and complex with the appearance of new applications and new protocols in Internet. We give a design to implement fine-granularity and configurable distributed measurement method of multi-protocol Traffic Behavior. Our study shows that probing points can be distributed to different the Functional Processing Module (FPM) along the Traffic path through the router, and each FPM can implement configurable and protocol-sensitive collection of packet information with accurate timing stamps. We develop a novel Traffic mirroring method to avoid affecting normal packet processing in case of some occasional failures. Our experiments based on practical implementation of measurement in a router show that less than 15% of total logic resources and less than 20 nanoseconds of timing precision can be achieved by our methods, which is more efficient and accurate than Special Packet capturing Card with an acceptable cost.
