Privacy Preserving Patient’s Health Monitoring Using Elliptic Curve Based IBE
The existing technique provides an address this important problem and designs a cloud-assisted privacy
preserving mobile health monitoring system to protect the privacy of the involved parties and their data. Moreover, the
outsourcing decryption technique and a newly proposed key private proxy re-encryption are adapted to shift the
computational complexity of the involved parties to the cloud without compromising clients’ privacy and service providers’
intellectual property. Finally, the security and performance analysis demonstrates the effectiveness of our proposed design.
Mobile health monitoring involves security and privacy of patient’s private data so that it can’t be access by the unauthorized
users. Mobile Health Monitoring contains various sensors to be used in the patient’s body so that 24*7 monitoring can be
done by the doctor. But the patient’s personal data is important and privacy is an important factor, hence various security
techniques are implemented for the security and privacy of patient’s private data. Here a new and efficient technique for
protecting the patient’s secure data using ECIES is proposed. The proposed technique implemented here provides less
computational cost and time and also provides security from various attacks as compared to the existing techniques.
Keywords- Cloud Computing, Elliptic Curves, Health Monitoring, Cloud Assistance, Cryptography.