Mining Human Activity Patterns from Smart Home Big Data for Healthcare Application


Mining Human Activity Patterns from Smart Home Big Data for Healthcare Application

S.Anitha, B.S.Sangeetha

S.Anitha, B.S.Sangeetha "Mining Human Activity Patterns from Smart Home Big Data for Healthcare Application" Published in International Journal of Trend in Research and Development (IJTRD), ISSN: 2394-9333, Special Issue | NCPCIT-18 , September 2018, URL: http://www.ijtrd.com/papers/IJTRD17998.pdf

The Distributed m-healthcare cloud computing system considerably facilitates secure and efficient patient treatment for medical consultation by sharing personal health information among the healthcare providers. This system should bring about the challenge of keeping both the data confidentiality and patients’ identity privacy simultaneously. Many existing access control and anonymous authentication schemes cannot be straightforwardly exploited. To solve the problem proposed a novel authorized accessible privacy model (AAPM) is established. Patients can authorize physicians by setting an access tree supporting flexible threshold predicates. Our new technique of attribute based designated verifier signature, a patient self-controllable multi-level privacy preserving cooperative authentication scheme (PSMPA) realizing three levels of security and privacy requirement in distributed m-healthcare cloud computing system is proposed. The directly authorized physicians, the indirectly authorized physicians and the unauthorized persons in medical consultation can respectively decipher the personal health information and/or verify patients’ identities by satisfying the access tree with their own attribute sets.

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Special Issue | NCPCIT-18 , September 2018

2394-9333

IJTRD17998