projects
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| In this project, the goal is to detect and visualize anomalies in dynamic graphs. Graphs are powerful tools to model networks and relationships between their entities. Many of the real-world graphs are dynamic in which nodes and edges are being added and deleted over time. Some of the dynamic network examples include social networks and computer networks. Anomalies are any deviation from the normal. For example, in a computer network, communications are normal over time until a single machine is attacked by a large number of other machines at a specific time point. We work on finding time points that an anomaly occurs and nodes, edges or subgraphs that are responsible for this anomalous behavior. This project focuses on finding and visualizing anomalies in a stream of graphs. The student will first use a visualization tool to visualize the network over time. This helps in better understanding the changes in the structure of the network. There are various visualization tools available to use for this purpose. In the second phase, the student will implement a graph anomaly detection method and combine it with the visualzation program so that the graph stream can be monitored through visualization and anomalies can be detected and illustrated in an online fashion. This project is a part of a collaborative project with IBM and the student will work closedly with a PhD student in the project. | In this project, the goal is to detect and visualize anomalies in dynamic graphs. Graphs are powerful tools to model networks and relationships between their entities. Many of the real-world graphs are dynamic in which nodes and edges are being added and deleted over time. Some of the dynamic network examples include social networks and computer networks. Anomalies are any deviation from the normal. For example, in a computer network, communications are normal over time until a single machine is attacked by a large number of other machines at a specific time point. We work on finding time points that an anomaly occurs and nodes, edges or subgraphs that are responsible for this anomalous behavior. This project focuses on finding and visualizing anomalies in a stream of graphs. The student will first use a visualization tool to visualize the network over time. This helps in better understanding the changes in the structure of the network. There are various visualization tools available to use for this purpose. In the second phase, the student will implement a graph anomaly detection method and combine it with the visualzation program so that the graph stream can be monitored through visualization and anomalies can be detected and illustrated in an online fashion. This project is a part of a collaborative project with IBM and the student will work closedly with a PhD student in the project. | ||
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| **Required skills:** Good programming skills in Python and Java. | **Required skills:** Good programming skills in Python and Java. | ||
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| **Recommended skills:** Experience with visualization tools is very helpful, Interest in algorithms for graphs. | **Recommended skills:** Experience with visualization tools is very helpful, Interest in algorithms for graphs. | ||
projects.txt · Last modified: 2018/05/07 14:39 by peterlian