Journal Title : International Journal of Modern Trends in Engineering and Science
Volume 03 Issue 05 2016
ISSN no: 2348-3121
Page no: 52-55
Abstract – The main objective of this research is ensuring the privacy as well as security by improving the fully homomorphic data aggregation. It is also focused to achieve the higher classification results in the disease detection. The existing method of PPDM is used to achieve the privacy in E-healthcare systems and proposed method of artificial neural network (ANN) algorithm is used to detect the disease more accurately. The proposed method increases the performance in terms of higher precision, recall and reduction in time complexity. The proposed system is done by using gray level co-occurrence matrix feature extraction and ANN approach. ANN method is used for identification of diseased images and improves the classification results significantly.
Keywords— Data Mining, Privacy Preservation, Security, Features Extraction and Classification
- Villalba, Elena, et al, Heart Failure monitoring system based on Wearable and Information Technologies, Journal of Communications 2.2 (2007): 10-21.
- Jung, Taeho, et al, Privacy-preserving data aggregation without secure channel: Multivariate polynomial evaluation, INFOCOM, 2013 Proceedings IEEE. IEEE, 2013.
- Bianchi, Tiziano, Alessandro Piva, and Mauro Barni, On the implementation of the discrete Fourier transform in the encrypted domain, Information Forensics and Security, IEEE Transactions on 4.1 (2009): 86-97.
- Castelluccia, Claude, et al, Efficient and provably secure aggregation of encrypted data in wireless sensor networks, ACM Transactions on Sensor Networks (TOSN) 5.3 (2009): 20.
- Kursawe, Klaus, George Danezis, and Markulf Kohlweiss, Privacy-friendly aggregation for the smart-grid, Privacy Enhancing Technologies, Springer Berlin Heidelberg, 2011.
- Zhou, Jun, and Zhenfu Cao, PSCPA: Patient Self-controllable Privacy-preserving Cooperative Authentication in Distributed m-Healthcare Systems, IACR Cryptology ePrint Archive 2012 (2012): 44.
- Erkin, Zekeriya, and Gene Tsudik, Private computation of spatial and temporal power consumption with smart meters, Applied Cryptography and Network Securit, Springer Berlin Heidelberg, 2012.
- Asaar, Maryam Rajabzadeh, Mahmoud Salmasizadeh, and Willy Susilo, Security Pitfalls of a Provably Secure Identity-based Multi-Proxy Signature Scheme.