http://www.iaeme.com/IJARET/index.asp 868 editor@iaeme.com International Journal of Advanced Research in Engineering and Technology (IJARET) Volume 11, Issue 12, December 2020, pp.868-877, Article ID: IJARET_11_12_086 Available online at http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=12 ISSN Print: 0976-6480 and ISSN Online: 0976-6499 DOI: 10.34218/IJARET.11.12.2020.086 © IAEME Publication Scopus Indexed CLOUD MALICIOUS THREAT DETECTION BY FEATURES FROM INTELLIGENT WATER DROP SET AND EBPN Rashmi Singh Phd Scholar, Computer Science Department of LNCT University, Bhopal, MP, India Dr. Praveen Kumar Mannepalli Computer Science Department of LNCT University, Bhopal, MP, India ABSTRACT Cloud increase strength of various organizations to work from any location and time. This flexibility lead to increase some security issue. As malicious programs take advantage of multiple entries in the cloud, so threat detection system need to be develop. This paper has developed a cloud malicious threat detection model which learns the behavior of different ideal and attack conditions. Requesting session on cloud has different feature set. So paper has filter those feature set by Intelligent Water Drop Set Algorithm (IWDA). Random feature set were developed in the algorithm for reducing the feature overload during training. Difference between the feature value act as soil in the algorithm for comparing two water drop sets. Filtered feature were passed in Error back propagation neural network where sigmoid function was used for training. Experiment was perform on UNSW-NB15 dataset and comparison result shows that proposed model has increase the threat detection accuracy by %. Key words: Anomaly Detection, Artificial Neural Network, Cloud Security, Classification. Cite this Article: Rashmi Singh and Praveen Kumar Mannepalli, Cloud Malicious Threat Detection by Features from Intelligent Water Drop Set and EBPN, International Journal of Advanced Research in Engineering and Technology, 11(12), 2020, pp. 868- 877. http://www.iaeme.com/IJARET/issues.asp?JType=IJARET&VType=11&IType=12 1. INTRODUCTION Network based work is naturally increasing from small enterprises to large organized companies as individual, private and government sector directly or indirectly depends on it for various technical solutions. Vulnerability on network functionality leads to loss of important information of individual, organization, community, nation, etc. Various kind of attacks take advantage of these compromised networks. So protection of those network from different malicious activities is highly demanding. Most of soft data and related services are shifted to