An organisation is more susceptible to a malicious insider threat. Because a malicious insider can have a significant negative impact on the data loss, it is essential to find them. Malicious insider threats are rare but extremely devastating. The primary goal of this research is to, identify the internal danger posed by hostile individuals in a business. Detecting malicious insider threats in cloud computing environment making use of Deep Convolutional Neural Network. Malicious insider threats are very hazardous to every cloud based organization. Detecting such threat is essential for ensuring security of an organization. Malicious insider threat incidents cause major damages to any organization. Earlier existing methods are lack in real time detection of threats. In this research work, Deep Convolutional Neural Network (DCNN) is utilized for enhancing security in cloud environment by combating against malicious insider threats and anomalies. It involves in the process of malicious insider threat prediction as well as classification malicious activity from non malicious activities. Anomaly score and threshold values are utilized for classifying threats from the legitimate environment.