公开(公告)号：US10129274B2

公开(公告)日：2018-11-13

申请号：US15273213

申请日：2016-09-22

申请人： Adobe Systems Incorporated

发明人： Suraj Satishkumar Sheth ,  Shagun Sodhani ,  Rohit Bajaj ,  Nitin Goel ,  Manoj Awasthi ,  Kapil Malik ,  Harsh Rathi ,  Balaji Krishnamurthy

IPC分类号： H04L29/06 ,  G06F17/30 ,  H04L12/26

摘要： In some embodiments, a processor accesses a metrics dataset, which includes metrics whose values indicate data network activity. The metrics dataset has segments. Each segment is a respective subset of the data items having a common feature. The processor identifies anomalous segments in the metrics dataset. Each anomalous segment has a segment trend that is different from a trend associated with the larger metrics dataset. The processor generates a data graph that includes nodes, which represent anomalous segments, and edges connecting the nodes. The processor applies weights to the edges. Each weight indicates (i) a similarity between a pair of anomalous segments represented by the nodes connected by the weighted edge and (ii) a relationship between the anomalous segments and the metrics dataset. The processor ranks the anomalous segments based on the applied weights and selects one or more segments with sufficiently high ranks.

公开(公告)号：US20180083995A1

公开(公告)日：2018-03-22

申请号：US15273213

申请日：2016-09-22

申请人： Adobe Systems Incorporated

发明人： Suraj Satishkumar Sheth ,  Shagun Sodhani ,  Rohit Bajaj ,  Nitin Goel ,  Manoj Awasthi ,  Kapil Malik ,  Harsh Rathi ,  Balaji Krishnamurthy

IPC分类号： H04L29/06 ,  G06F17/30

CPC分类号： H04L63/1416 ,  G06F17/3089 ,  G06F17/30958 ,  H04L41/0631 ,  H04L43/08

摘要： In some embodiments, a processor accesses a metrics dataset, which includes metrics whose values indicate data network activity. The metrics dataset has segments. Each segment is a respective subset of the data items having a common feature. The processor identifies anomalous segments in the metrics dataset. Each anomalous segment has a segment trend that is different from a trend associated with the larger metrics dataset. The processor generates a data graph that includes nodes, which represent anomalous segments, and edges connecting the nodes. The processor applies weights to the edges. Each weight indicates (i) a similarity between a pair of anomalous segments represented by the nodes connected by the weighted edge and (ii) a relationship between the anomalous segments and the metrics dataset. The processor ranks the anomalous segments based on the applied weights and selects one or more segments with sufficiently high ranks.