Netzwerk: Migration of a Packet-Switching Network Simulation Environment from MS Windows PC to Linux PC and to HPC

Ławniczak, Anna T.; Gerisch, Alf; Maxie, K.P.; Stefano, Bruno N. Di

doi:10.1109/hpcs.2005.35

Cited by 7 publications

(12 citation statements)

References 11 publications

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“…We briefly describe the PSN model, developed in [16], [17], and its C++ simulator, called Netzwerk-1 ( [18], [19]) that we use in our study. The PSN model is an abstraction of the ISO OSI Network Layer Reference Model.…”

Section: A Packet Switching Network Modelmentioning

confidence: 99%

Detection of stationary network load increase using univariate network aggregate traffic data by dynamic PCA

Xie

Ławniczak

2011

2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

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Network operators are now facing bandwidth outages as well as a growing pressure to ensure good Quality of Service (QoS). An important practical issue for network service providers is to pay close attention to the load changes of network traffic, in particular, the stationary increase of load from a normal demand. Many network monitoring applications and performance analysis tools are based on the study of an aggregate measure of network traffic, e.g. number of packets in transit (NPT), which is a long-term univariate time series. To classify this type of network traffic data and detect any increase of network source load, we propose a dynamic principal component analysis (PCA) method, first to extract data features and then to detect a stationary load increase of network traffic. The proposed detection schemes are based on either the major or the minor principal components of network traffic data. To demonstrate the applications of the proposed feature extraction method and the detection schemes, we applied them to network traffic data simulated from the packet switching network (PSN) model. Additionally, we propose a combined detection scheme that uses both the major and the minor principal components. The proposed detection schemes, based on dynamic PCA, show enhanced performance in detecting an increase of network load for the simulated network traffic data. These results offer a new feature extraction method based on dynamic PCA that creates additional feature variables for event detection in a univariate time series.

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Section: A Packet Switching Network Modelmentioning

confidence: 99%

Detection of stationary network load increase using univariate network aggregate traffic data by dynamic PCA

Xie

Ławniczak

2011

2011 IEEE Symposium on Computational Intelligence for Security and Defense Applications (CISDA)

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“…We briefly describe the PSN model, developed in [5,6], and its C++ simulator, called Netzwerk-1 [10,11] that we use in our study. The PSN model is an abstraction of the ISO OSI Network Layer Reference Model.…”

Section: Description Of Packet Switching Network Modelmentioning

confidence: 99%

“…In Section 2, we describe briefly the PSN model used in our study [5,6,10,11]. In Section 3, we describe the experiments that we conducted using the PSN model and we introduce network performance indicators used in our study [12].…”

Section: Introductionmentioning

confidence: 99%

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Impact of source load and routing on QoS of packets delivery

Ławniczak

Xie

2010

Journal of Computational Science

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“…First, we briefly describe our PSN model ( [9], [10]), its C++ simulator, Netzwerk ( [11], [12]]), and explain how they have been customized to model and simulate a "ping" type DDoS attacks. Next, we introduce definition of entropy functions of network-wide monitored packet traffic at selected sets of routers used by us in detection of DDoS attacks in our virtual experiments.…”

Section: Introductionmentioning

confidence: 99%

Detection of anomalous packet traffic via entropy

Ławniczak

Stefano³

2009

2009 Canadian Conference on Electrical and Computer Engineering

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We study if information entropy of packet traffic passing through selected set of routers may detect anomalous packet traffic (e.g., distributed denial-of-service (DDoS) attacks) in a packet switching network (PSN) model. Given a certain PSN model setup (i.e., topology, routing algorithm, and source load value) a "natural" entropy profile of normal packet traffic monitored at selected routers characterizes normal operation of PSN model. When entropy of packet traffic deviates significantly from this "natural" profile it means that some anomaly in packet traffic emerges. Our simulations of ping DDoS attacks show that after start of attacks the entropy of packet traffics monitored networkwide at relatively small sets of routers may significantly drop and that it is easier to detect these drops if static routing is used instead of dynamic routing. Thus, for detection of DDoS attacks and other anomalous packet traffic information entropy of packet traffic monitored network-wide at properly selected routers can be a useful tool.Index Terms -distributed denial of service attack, detection, packet switching network, entropy

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Netzwerk: Migration of a Packet-Switching Network Simulation Environment from MS Windows PC to Linux PC and to HPC

Cited by 7 publications

References 11 publications

Detection of stationary network load increase using univariate network aggregate traffic data by dynamic PCA

Detection of stationary network load increase using univariate network aggregate traffic data by dynamic PCA

Impact of source load and routing on QoS of packets delivery

Detection of anomalous packet traffic via entropy

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