Enhanced Honeypot cryptographic scheme and privacy preservation for an effective prediction in cloud security

Abstract For the cloud security or intrusion detection system (IDS) an effective scheme for prediction and privacy preservation is employed with the use of enhanced Honeypot algorithm. At first, the dataset is preprocessed with the use of normalization method at which the missing values were replaced and an unwanted data will be removed. After that, features are extracted and best features were selected with the use of GLCM algorithm. The classifier is then accountable for the prediction of target and a novel CNN classifier is used for this which in turn offers high rate of accuracy in the prediction of attack. The data is then kept in the server of cloud for monitoring and maintenance purpose. It is vital to keep and secure the data from an intrusion or any other attack. In order tocontent this scheme of privacy reservation, a technique of cryptography isused in this approach. The Honeypot algorithm of cryptography is utilized for the use of encryption. As, the data owner requests for the file, the cloud server is then responsible for key generation and to verify this key with user for the purpose of authentication. After the provision of key, the file is decrypted using Honeypot algorithm and a decrypted file will be retrieved by the user. In conclusion, the performance analysis is carried and the comparative analysis of existing and proposed techniques is made for proving the proposed scheme effectiveness.