Regressive Based Classifier Analytics for the Mechanism of CryptoSystems Security Using EHE Scheme

Due to the improvement in digital technologies, the security of the data gets into drastic trouble. Several type of encryption-based algorithm has been initiated which tended to be insecure and procure threats to the digital world. To avoid the flaws in the digital era, the researchers brought up new encryption algorithm in existing framework. For a better accuracy purpose, support vector machine algorithm has been developed to provide image-oriented encryption. Some of the parameters are been detected to categorize the image dataset. Machine learning can be used to process large amount of vast data. SVM is used to classify each dataset in different aspects. Here in this paper, the enhanced homo morphic encryption (EHE) is used. Logistic regression provides less precise loss by classifying it. Data gets supervised since logistic regression does not have closed solution. Based on classification, it determines whether the data is been secured or violated. EHE is used for computation on the already encrypted data without assuming the value. For the efficient way of securing message transmission in mobile ad hoc network EHE is used.