• Krishna Prajapati

Data Mining is an efficient data analysis process which is used to find the patterns and relationship of a large database. Clustering is a popular technique of data mining for unsupervised learning in which labels are not defined previously. Anomaly detection is a problem of finding unexpected patterns in a dataset. Unexpected patterns can be defined as those that do not conform to the general behavior of the dataset. Anomaly detection is important for several application domains such as financial and communication services, public health, and climate studies.

k-means 2-tier clustering Algorithm

"A PROPOSED ARCHITECTURE OF ANOMALY DETECTION USING K-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.478-481, May-2019, Available :http://www.jetir.org/papers/JETIR1905J70.pdf

"A PROPOSED ARCHITECTURE OF ANOMALY DETECTION USING K-MEANS CLUSTERING ALGORITHM", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp478-481, May-2019, Available at : http://www.jetir.org/papers/JETIR1905J70.pdf