TY - GEN
T1 - Spatial-Temporal Anomaly Detection Using Security Visual Analytics via Entropy Graph and Eigen Matrix
AU - Sinda, Matthew
AU - Liao, Qi
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2018/3/29
Y1 - 2018/3/29
N2 - Much of the big data which is produced is due to IoT devices and various sensor networks. This data often comes with spatial as well as temporal properties that can tell investigators many things about the environment in which they are located. For security practitioners, how to find abnormal activities or anomalies in the vast amount of spatial-temporal dynamic data is a daunting task. We present a system, STAnD, to assist investigators in determining patterns within these spatial-temporal data sets. The analysis conducted by using this program can support correlating events in both the spatial and temporal domains which will lead the investigators to determine probable causes for potential malicious events.
AB - Much of the big data which is produced is due to IoT devices and various sensor networks. This data often comes with spatial as well as temporal properties that can tell investigators many things about the environment in which they are located. For security practitioners, how to find abnormal activities or anomalies in the vast amount of spatial-temporal dynamic data is a daunting task. We present a system, STAnD, to assist investigators in determining patterns within these spatial-temporal data sets. The analysis conducted by using this program can support correlating events in both the spatial and temporal domains which will lead the investigators to determine probable causes for potential malicious events.
KW - big data analytics
KW - eigenvectors
KW - entropy graph
KW - security visualization
KW - spatial-temporal anomaly detection
UR - http://www.scopus.com/inward/record.url?scp=85048091894&partnerID=8YFLogxK
U2 - 10.1109/DASC-PICom-DataCom-CyberSciTec.2017.95
DO - 10.1109/DASC-PICom-DataCom-CyberSciTec.2017.95
M3 - Conference contribution
AN - SCOPUS:85048091894
T3 - Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017
SP - 511
EP - 518
BT - Proceedings - 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Dependable, Autonomic and Secure Computing, 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing, 2017 IEEE 3rd International Conference on Big Data Intelligence and Computing and 2017 IEEE Cyber Science and Technology Congress, DASC-PICom-DataCom-CyberSciTec 2017
Y2 - 6 November 2017 through 11 November 2017
ER -