TY - GEN
T1 - Sequential anomaly detection with observation control
AU - Tsopelakos, Aristomenis
AU - Fellouris, Georgios
AU - Veeravalli, Venugopal V.
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - The problem of anomaly detection is considered when multiple processes are observed sequentially, but it is possible to sample only a subset of them at a time according to an adaptive sampling policy. The problem is to stop sampling as soon as possible and identify the anomalous processes, while controlling appropriate error probabilities. We consider two versions of this problem: in the first one there is no assumption regarding the anomalous processes, in the second their number is assumed to be known a priori. For each version, we obtain the optimal asymptotic performance as the error probabilities vanish and characterize the sampling rules that lead to asymptotic optimality. Moreover, we present two sampling rules for each setup, which differ in terms of the computational complexity and the actual performance they imply.
AB - The problem of anomaly detection is considered when multiple processes are observed sequentially, but it is possible to sample only a subset of them at a time according to an adaptive sampling policy. The problem is to stop sampling as soon as possible and identify the anomalous processes, while controlling appropriate error probabilities. We consider two versions of this problem: in the first one there is no assumption regarding the anomalous processes, in the second their number is assumed to be known a priori. For each version, we obtain the optimal asymptotic performance as the error probabilities vanish and characterize the sampling rules that lead to asymptotic optimality. Moreover, we present two sampling rules for each setup, which differ in terms of the computational complexity and the actual performance they imply.
KW - Anomaly detection
KW - asymptotic optimality
KW - outlying sequence detection
KW - sequential design of experiments
UR - http://www.scopus.com/inward/record.url?scp=85073168113&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85073168113&partnerID=8YFLogxK
U2 - 10.1109/ISIT.2019.8849555
DO - 10.1109/ISIT.2019.8849555
M3 - Conference contribution
AN - SCOPUS:85073168113
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 2389
EP - 2393
BT - 2019 IEEE International Symposium on Information Theory, ISIT 2019 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE International Symposium on Information Theory, ISIT 2019
Y2 - 7 July 2019 through 12 July 2019
ER -