Secure and Efficient Data Sharing in Cloudlet Based Healthcare System Using NTRU and Bloom Filter
B. Santosh Kumar1, M. Raghavendra Reddy2
1B. Santosh Kumar, Assistant Professor, G.Pulla Reddy Engineering College, Kurnool (A.P), India.
2M. Raghavendra Reddy, Assistant Professor, G.Pulla Reddy Engineering College, Kurnool (A.P), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 32-35| Volume-8 Issue-6, April 2019 | Retrieval Number: F1017048619/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Healthcare social platform, together with Patients LikeMe, can achieve data from further related sufferers by information distribution in phrases of individual’s personal results. Yet distributing scientific information on the social community is useful to both sufferers & physicians, the susceptible records is probably revealed or thieve, which reasons seclusion & protection issues without competent safety for the shared data. In this paper, we increase a fresh healthcare system through exploiting the power of cloudlet and also utilizing Bloom filter hashing for security. The operations of cloudlet contain seclusion defense, information distributing & intrusion discovery. The body data accumulated via wearable gadgets is broadcasted to the closer cloudlet. Those data are in addition added to the remote cloud wherein medical physicians can get right of entry to sickness analysis.
Keyword: Cloudlet, Data Collection, Intrusion Detection.
Scope of the Article: Big Data Quality Validation