Author : Paridhi Jain and Prof. Rashmi Tundalwar

Social Media Health Networks give a promising worldview to pull in patients to share and impart their individual health status with other online patients, and counsel healthcare administrations from online guardians with social systems. Social Media Health Networks change healthcare administrations from tedious disconnected medical clinic focused worldview to the advantageous and productive online worldview through web, which can extend the conventional healthcare benefits and abbreviate the data hole among patients and guardians. In any case, how to assemble the trust among patients and parental figures raises a testing issue because of the transparency of the social systems, in the interim the individual security might be unveiled when sharing individual health data with different patients and parental figures. In this work, we propose a customized and confided in healthcare administration way to deal with empower trusted and protection saving healthcare benefits in social media health systems, which can improve the trustiness among patients and parental figures through bona fide evaluations towards parental figures and assurance the patients’ security. In particular, we utilize the collective sifting model to look for suitable customized parental figures, blossom channel to remove and map the individual healthcare side effects, and inward item to register the similitude between patients for discovering patients with comparable health manifestations in a security saving way. In the interim, to ensure real evaluations and surveys towards parental figures, we build up a sybil attack identification plan to locate patients’ phony evaluations and surveys utilizing various nom de plumes. Security examination shows that our proposed approach can save the protection of patients and forestall sybil attacks. Execution assessment exhibits that our methodology can accomplish conspicuous execution improvement, regarding customized guardians finding furthermore, sybil attack opposition.

Keywords: Physician patient relationships, health behavior, social  media, social theory, psychological theory, medical informatics