Custom Query (1408 matches)
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Ticket | Resolution | Summary | Owner | Reporter |
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#1377 | fixed | Experimentation of SDN-Supported Collaborative DDoS Attack Detection and Containment | ||
Description |
Demo Title: "Experimentation of SDN-Supported Collaborative DDoS Attack Detection and Containment" Tommy Chin, Xenia Mountrouidou, Xiangyang Li, Kaiqi Xiong One-sentence layman's description:
Who should see this demo?
Software-defined networking (SDN) and OpenFlow offer great support to dynamically adapt a network and to access data on different network layers as needed. Such advantages have been driving recent research efforts to develop new security applications and services. However, most studies on attack detection and containment have not really differentiated their solutions from the traditional ones, without fully taking advantage of the unique capabilities provided by SDN. Moreover, even if some of these studies provide interesting visions of what can be achieved, they stop short of presenting realistic application scenarios and experimental results. We present a novel attack detection and containment approach that is coordinated by distributed network monitors and controllers/correlators centralized on an SDN OpenFlow Virtual Switch (OVS). With different views and information availability, these elements collaboratively detect signature constituents of an attack that possess different characteristics of scale and detail. Therefore, this approach is able to not only quickly issue an alert against potential threats followed by careful verification for high accuracy, but also balance the workload on the OVS. We apply the proposed approach to TCP SYN flood attacks using Global Environment for Network Innovations (GENI). This realistic experimentation has provided us with insightful findings helpful to our goal toward a systematic methodology of SDN-supported attack detection and containment. First, we have demonstrated through experimentation the scalability of our collaborative scheme. Second, we have studied how the combination of alerts by the monitor and deep packet inspection by the correlator, can increase the speed and accuracy of attack identification. Our experiments, in the context of a small to medium corporate network, have demonstrated the effectiveness and scalability of the SDN-supported detection and containment approach..
One VLAN for single network connection
N/A
N/A
VGA Monitor with minimal of resolution of 1440x900 or 1280x1024
One
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#1376 | fixed | Demo Registration - GEC 22 | ||
Description |
Demo Title: "Experimentation of SDN-Supported Collaborative DDoS Attack Detection and Containment" Tommy Chin, Xenia Mountrouidou, Xiangyang Li, Kaiqi Xiong One-sentence layman's description:
Who should see this demo?
Software-defined networking (SDN) and OpenFlow offer great support to dynamically adapt a network and to access data on different network layers as needed. Such advantages have been driving recent research efforts to develop new security applications and services. However, most studies on attack detection and containment have not really differentiated their solutions from the traditional ones, without fully taking advantage of the unique capabilities provided by SDN. Moreover, even if some of these studies provide interesting visions of what can be achieved, they stop short of presenting realistic application scenarios and experimental results. We present a novel attack detection and containment approach that is coordinated by distributed network monitors and controllers/correlators centralized on an SDN OpenFlow Virtual Switch (OVS). With different views and information availability, these elements collaboratively detect signature constituents of an attack that possess different characteristics of scale and detail. Therefore, this approach is able to not only quickly issue an alert against potential threats followed by careful verification for high accuracy, but also balance the workload on the OVS. We apply the proposed approach to TCP SYN flood attacks using Global Environment for Network Innovations (GENI). This realistic experimentation has provided us with insightful findings helpful to our goal toward a systematic methodology of SDN-supported attack detection and containment. First, we have demonstrated through experimentation the scalability of our collaborative scheme. Second, we have studied how the combination of alerts by the monitor and deep packet inspection by the correlator, can increase the speed and accuracy of attack identification. Our experiments, in the context of a small to medium corporate network, have demonstrated the effectiveness and scalability of the SDN-supported detection and containment approach..
One VLAN for single network connection
N/A
N/A
VGA Monitor with minimal of resolution of 1440x900 or 1280x1024
One
|
|||
#1375 | fixed | Demo Registration - GEC 22 | ||
Description |
Demo Title: Experimentation of SDN-Supported Collaborative DDoS Attack Detection and Containment Tommy Chin, Xenia Mountrouidou, Xiangyang Li, Kaiqi Xiong One-sentence layman's description:
Who should see this demo?
Software-defined networking (SDN) and OpenFlow offer great support to dynamically adapt a network and to access data on different network layers as needed. Such advantages have been driving recent research efforts to develop new security applications and services. However, most studies on attack detection and containment have not really differentiated their solutions from the traditional ones, without fully taking advantage of the unique capabilities provided by SDN. Moreover, even if some of these studies provide interesting visions of what can be achieved, they stop short of presenting realistic application scenarios and experimental results. We present a novel attack detection and containment approach that is coordinated by distributed network monitors and controllers/correlators centralized on an SDN OpenFlow Virtual Switch (OVS). With different views and information availability, these elements collaboratively detect signature constituents of an attack that possess different characteristics of scale and detail. Therefore, this approach is able to not only quickly issue an alert against potential threats followed by careful verification for high accuracy, but also balance the workload on the OVS. We apply the proposed approach to TCP SYN flood attacks using Global Environment for Network Innovations (GENI). This realistic experimentation has provided us with insightful findings helpful to our goal toward a systematic methodology of SDN-supported attack detection and containment. First, we have demonstrated through experimentation the scalability of our collaborative scheme. Second, we have studied how the combination of alerts by the monitor and deep packet inspection by the correlator, can increase the speed and accuracy of attack identification. Our experiments, in the context of a small to medium corporate network, have demonstrated the effectiveness and scalability of the SDN-supported detection and containment approach..
One VLAN for single network connection
N/A
N/A
VGA Monitor with minimal of resolution of 1440x900 or 1280x1024
One
|