A scalable and efficient methodology for flow monitoring in the Internet

Molina, Maurizio

doi:10.1016/s1388-3437(03)80172-5

Cited by 7 publications

(3 citation statements)

References 9 publications

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“…A further algorithm that fits into the category of non-uniform flow state dependent Sampling is described in [Moli03].…”

Section: Non-uniform Flow State Dependent Samplingmentioning

confidence: 99%

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Sampling and Filtering Techniques for IP Packet Selection

Zseby¹,

Molina²,

Duffield³

et al. 2009

121

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“…A further algorithm that fits into the category of non-uniform flow state dependent Sampling is described in [Moli03].…”

Section: Non-uniform Flow State Dependent Samplingmentioning

confidence: 99%

“…Some concrete proposals for such methods exist from the research community (e.g., [EsVa01], [DuLT01], [Moli03]). Some of these proposals are still in an early stage and need further investigations to prove their usefulness and applicability.…”

Section: Configuration Of Non-uniform Probabilistic and Flow State Samentioning

confidence: 99%

Sampling and Filtering Techniques for IP Packet Selection

Zseby¹,

Molina²,

Duffield³

et al. 2009

121

View full text Add to dashboard Cite

“…Flow monitoring [1] provides statistical measures of packet flows described by common properties, e.g. by the IP-5-tuple [18]. Depending on the specification of the flow characteristics, the necessary bandwidth to transport all monitoring data can be successfully reduced at cost of granularity and content.…”

Section: Introductionmentioning

confidence: 99%

Bio-inspired promoters and inhibitors for self-organized network security facilities

Dressler

2006

Proceedings of the 1st International Conference on Bio Inspired Models of Network, Information and Computing Systems - BIONETI

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Self-organization techniques based on promoters and inhibitors has been intensively studied in biological systems. Promoters enable an on-demand amplification of reactions to a particular cause. This allows to react quickly with appropriate countermeasures. On the other hand, inhibitors are capable of regulating this uncontrolled amplification by suppressing the reaction. In this paper, we demonstrate the applicability of these mechanisms in a network security scenario consisting of network monitoring elements, attack detection, and firewall devices. Previous work identified most existing detection approaches as not suitable for high-speed networks. This problem can be alleviated by separating the methodologies for network monitoring and for subsequent data analysis. In this paper, we present an adaptation algorithm that allows to manage the individual configuration parameters in order to optimize the overall system. We show the advantages of self-regulating techniques based on promoters and inhibitors that lead to maximized security and that gracefully degradate in case of overload situations. We created a simulation model to verify the algorithms. The results of the conducted simulations encourage further studies in this field.

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Self-Organized Network Security Facilities based on Bio-inspired Promoters and Inhibitors

Dressler

2007

Advances in Biologically Inspired Information Systems

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A scalable and efficient methodology for flow monitoring in the Internet

Cited by 7 publications

References 9 publications

Sampling and Filtering Techniques for IP Packet Selection

Sampling and Filtering Techniques for IP Packet Selection

Bio-inspired promoters and inhibitors for self-organized network security facilities

Self-Organized Network Security Facilities based on Bio-inspired Promoters and Inhibitors

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