Abstrakt

Privacy Preserving & Access Control to Intrusion Detection in Cloud System

Swati P. Ramteke, Priya S. Karemore, S. S. Golait

As Cloud Computing becomes common, more and more responsive information are being centralized into the cloud. For the protection of data privacy, sensitive data usually have to be encrypted before outsourcing, which makes effectual data utilization, a very challenging task. We propose a new model for data storage and access in clouds. Our scheme avoids storing multiple encrypted copies of same data. In our framework for secure data storage, cloud stores encrypted data (without being able to decrypt them). The main innovation of our model is addition of key distribution centers (KDCs). In this paper, we propose a solution which removes the trusted central authority, and protects the users privacy by preventing the authorities from pooling their information on particular users, thus making ABE more usable in practice. To handle large scale network access traffic and administrative control of data and application in cloud, a new multi-threaded distributed cloud IDS model has been proposed. Our proposed cloud IDS handles large flow of data packets, analyze them and generate reports efficiently by integrating knowledge and behavior analysis to detect intrusions.