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In this episode of PING, Professor Cristel Pelsser who holds the chair of critical embedded systems at UCLouvain Discusses her work measuring BGP and in particular the system described in the 2024 SIGCOMM “best paper” award winning research: “The Next Generation of BGP Data Collection Platforms”
Cristel and her collaborators Thomas Alfroy, Thomas Holterbach, Thomas Krenc and K. C. Claffy have built a system they call GILL, available on the web at https://bgproutes.io This work also features a new service called MVP, to help find the “most valuable vantage point” in the BGP collection system for your particular needs. GILL has been designed for scale, and will be capable of encompassing thousands of peerings. it also has an innovative approach to holding BGP data, focussed on the removal of demonstrably redundant information, and therefore significantly higher compression of the data stream compared to e.g. holding MRT files.
The MVP system exploits machine learning methods to aide in the selection of the most advantageous data collection point reflecting a researchers specific needs. Application of ML methods here permits a significant amount of data to be managed and change reflected in the selection of vantage points.
Their system has already been able to support DFOH, an approach to finding forged origin attacks from peering relationships seen online in BGP, as opposed to the peering expected both from location, and declarations of intent inside systems like peeringDB.
Read more about Cristel’s work, and their BGP analysis tools on the web:
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In this episode of PING, Professor Cristel Pelsser who holds the chair of critical embedded systems at UCLouvain Discusses her work measuring BGP and in particular the system described in the 2024 SIGCOMM “best paper” award winning research: “The Next Generation of BGP Data Collection Platforms”
Cristel and her collaborators Thomas Alfroy, Thomas Holterbach, Thomas Krenc and K. C. Claffy have built a system they call GILL, available on the web at https://bgproutes.io This work also features a new service called MVP, to help find the “most valuable vantage point” in the BGP collection system for your particular needs. GILL has been designed for scale, and will be capable of encompassing thousands of peerings. it also has an innovative approach to holding BGP data, focussed on the removal of demonstrably redundant information, and therefore significantly higher compression of the data stream compared to e.g. holding MRT files.
The MVP system exploits machine learning methods to aide in the selection of the most advantageous data collection point reflecting a researchers specific needs. Application of ML methods here permits a significant amount of data to be managed and change reflected in the selection of vantage points.
Their system has already been able to support DFOH, an approach to finding forged origin attacks from peering relationships seen online in BGP, as opposed to the peering expected both from location, and declarations of intent inside systems like peeringDB.
Read more about Cristel’s work, and their BGP analysis tools on the web:
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