Secure Data Sharing with Flexible User Access Privilege Update in Cloud-assisted IoMT
ABSTARCT :
Cloud-assisted Internet of Medical Things (IoMT) is becoming an emerging paradigm in the healthcare domain, which involves collection, storage and usage of the medical data. Considering the confidentiality and accessibility of the outsourced data, secure and fine-grained data sharing is a crucial requirement for the patients. Attribute-based encryption (ABE) is a promising solution to deal with this issue, but considering its property of each attribute sharing with multiple users, how to flexibly and efficiently update access privileges of certain users without affecting others is still a serious challenge. In this paper, we propose a secure and fine-grained data sharing scheme with flexible user access privilege update in cloud-assisted IoMT environment. Specifically, we take ABE as the basic building block, and utilize proxy re-encryption and key blinding techniques to empower the cloud server to re-encrypt the ciphertext affected by revocation and update keys for unrevoked users. In addition, adding attributes for users to extend their access rights is realized only based on few key components stored in cloud without entirely re-computing and re-issuing keys for them. As a result, the patients are able to flexibly and efficiently share their data and manage users' privileges. Formal proof and detailed performance evaluation demonstrate the security and efficiency of the proposed scheme.
EXISTING SYSTEM :
? In this paper, we focused on a thorough review of current and existing literature on different approaches and mechanisms used in e-Health to deal with security and privacy issues.
? Data are exposed to different threats when organizations assume that cloud migration is a “lift-and-shift” endeavor of simply porting their existing IT stack and security controls to a cloud environment.
? We have studied the existing PKE, IBE, IBBE, & ABE and then proposed multiple solutions to safeguard cloud-based data in ehealth systems.
? This review highlights a comprehensive study of existing cloud-based eHealth solutions that are cryptographic and non-cryptographic methods for protecting the privacy and security of digital data.
DISADVANTAGE :
? The solution of the problem is a degree constraint, that is crucial for realism in both contexts several other greedy heuristics to solve the online problem.
? Current hypervisors don’t provide adequate provision because of synchronization problems and soft real-time constraints which result in frequent serious performance degradation and deadline misses.
? When there is a new problem based on past experience used CBR to find a solution.
? This has increased the vital security problem of how to control and anticipate unapproved access to information stored in the cloud.
? The author proposed an algorithm SEQ that tells about resource augmentation to give a solution to Maximize Throughput Bounded Degree (MTBD) problem.
PROPOSED SYSTEM :
• An integrated blockchain model of a fully independent blockchain (FPB) and consortium blockchain (CB) was proposed to improve the time taken for data validation.
• While considering the future and growth of cloud-based healthcare services, we focused on the security of critical electronic health records (EHRs) and proposed an identity-based secure and encrypted data-sharing technique.
• We have studied the existing PKE, IBE, IBBE, & ABE and then proposed multiple solutions to safeguard cloud-based data in ehealth systems.
• Specialists have developed a system for IoT-based shrewd well-being systems used in their proposal as an e-Health platform, zeroing in on interoperability, different criteria for creativity, correspondence protocols, and framework prerequisites.
ADVANTAGE :
? The researchers have been anticipated this is the active load balance strategy has a number of constraints with respect to performance time and memory requirement.
? Distribution of cloud environment; dynamic load scheduling module which proposes a hybrid load balance algorithm to realize high performance load balance for cloud center.
? Performance analysis and extensive security demonstrate the plans are secure and exceedingly proficient.
? Performance assessment of assignment models and Cloud provisioning algorithms in a repeatable way beneath various designs prerequisites is an issue.
? The energy is reduced using Energy-Efficient Virtual Machines Scheduling in Multi-Tenant Data Centers.
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