期刊名称：Lecture Notes in Engineering and Computer Science
印刷版ISSN：2078-0958
电子版ISSN：2078-0966
出版年度：2018
卷号：2231&2232
页码：131-136
出版社：Newswood and International Association of Engineers
摘要：An anomaly (deviant objects, exceptions, peculiar
objects) is an important concept of the analysis. The volume
and velocity of the data within many systems makes it difficult
to detect and process anomalies for Big Data in real-time.
Many anomaly detective systems count on the historical data
for detecting behaviors’. Considering it as a problem to
financial institutions in Ghana, the researcher proposed robust
anomaly detection framework. The proposed frame work
defines Spark stream, as part of Spark ecosystem, which
stream data in real-time. Also, the proposed framework data
model was build using SVM, Linear regression and Logistic
regression as a package found in Spark MLlib. Additionally,
the proposed framework was explained clearly to be
implemented in real systems for financial institutions.
