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Cloud Computing is an Internet based Computing where virtual shared servers provide software, infrastructure, platform and other resources to the customer on pay-as-you-use basis. With the enormous use of Cloud, the probability of occurring intrusion also increases. Intrusion Detection System (IDS) is a stronger strategy to provide security. In this paper, we have proposed an efficient, fast and secure IDS with the collaboration of multi-threaded Network Intrusion Detection System (NIDS) and Host Intrusion Detection System (HIDS). In the existing system, Cloud-IDS capture packets from Network, analyze them and send reports to the Cloud Administrator on the basis of analysis. Analysis of packets is done using K-Nearest Neighbor and Neural Network (KNN-NN) hybrid classifier. For training and testing purpose here we have used NSL-KDD dataset. After getting the report from the Cloud-IDS, Cloud Service Provider (CSP) will generate an alert for the user as well as maintain a loglist for storing the malicious IP addresses. Our proposed model handles large flow of data packets, analyze them and generate reports efficiently integrating anomaly and misuse detection.

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