A mixed clustering approach for real-time anomaly detection

HIGHLIGHTS

• who: Fokrul Alom Mazarbhuiya and Mohamed Shenify from the School of Fundamental and Applied Sciences, Assam Don Bosco University, Guwahati, India have published the Article: A Mixed Clustering Approach for Real-Time Anomaly Detection, in the Journal: (JOURNAL)
• what: In this Article a mixed clustering approach is introduced for this purpose which also takes attributes into consideration. In , an algorithm was proposed, which can detect anomalies from datasets with mixed attributes. The aim of this article is as follows. In this article, a clustering-based anomaly detection algorithm is proposed for realthis article, a clustering . . .
  

   

  

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