An Adaptive Slide Window Security Method for Transaction Updation in Data Stream Mining

Data steam mining has gained large interest in current research domain. Where various information’s are retrieved based on the content of the context, the accuracy of the input stream with respect to its privacy is a major challenge. Windowing technique is used an effective approach in providing security measure in data stream mining. The recent develop windowing approach operates using sliding window, where anonymity is focused by different processing rules. The linear search sliding window has a constraint of search overhead and loss of generality under distributed information. In this paper, a new adaptive window approach for privacy coding in data stream mining is proposed. This presented approach is developed with the concern of minimize the search overhead and accuracy in search mining performance using adaptive window monitoring.