0000000000909514
AUTHOR
Justin Zhan
Anomaly Detection in Dynamic Social Systems Using Weak Estimators
Anomaly detection involves identifying observationsthat deviate from the normal behavior of a system. One ofthe ways to achieve this is by identifying the phenomena thatcharacterize “normal” observations. Subsequently, based on thecharacteristics of data learned from the “normal” observations,new observations are classified as being either “normal” or not.Most state-of-the-art approaches, especially those which belongto the family parameterized statistical schemes, work under theassumption that the underlying distributions of the observationsare stationary. That is, they assume that the distributions thatare learned during the training (or learning) phase, thoughunknown, are not time-varyin…
Anomaly detection in dynamic systems using weak estimators
Accepted version of an article from the journal: ACM transactions on internet technology. Published version available from the ACM: http://dx.doi.org/10.1145/1993083.1993086 Anomaly detection involves identifying observations that deviate from the normal behavior of a system. One of the ways to achieve this is by identifying the phenomena that characterize “normal” observations. Subsequently, based on the characteristics of data learned from the “normal” observations, new observations are classified as being either “normal” or not. Most state-of-the-art approaches, especially those which belong to the family of parameterized statistical schemes, work under the assumption that the underlying…