scholarly journals Ascendable and Protected Allocation of Personal Health Records in Cloud Computing Expending Multi Ability Attribute-Based Encryption

2019 ◽  
Vol 8 (2S8) ◽  
pp. 908-914
Keyword(s):  
Distributed Computing ◽  
Well Being ◽  
Personal Health ◽  
Sensitive Information ◽  
Human Beings ◽  
Health Records ◽  
Know How ◽  
Attribute Based Encryption ◽  
Cloud Server ◽  
Specific Association

character fitness document (PHR) is stored up within the integrated server to keep up the affected person's near domestic andPHR administrations are redistributed to outsider professional co-ops. The essential trouble is prepared analysis information. The affected individual facts ought to be whether the patients must actually manipulate the imparting saved up to immoderate protection and security. the safety plans are carried out to shield the character information from unfastened. Tolerant records can be gotten to through diverse human beings. each expert is alloted with get right of entry to consent for a specific association of residences. the doorway manage and safety the board is an unpredictable project in the affected character well-being record the executives approach. allotted computing is a conversational articulation used to painting a large kind of types of registering thoughts that encompass infinite desktops which may be associated via a continuous correspondence organize. it's miles an equal word for disseminated processing over a tool and manner the capacity to run a software program on many associated computer systems concurrently. statistics proprietors replace the person facts into outsider cloud server farms. The story know-how driven machine and a set of facts get to components to manipulate PHRs placed away in semi-confided in servers. to perform outstanding-grained and flexible statistics get access to control for PHRs, we effect function based absolutely Encryption (ABE) structures to scramble every affected man or woman's PHR file. severa information proprietors can get to similar statistics esteems. The proposed plan may be reached out to Multi Authority feature primarily based Encryption (MA-ABE) for numerous expert primarily based get right of entry to manipulate mechanism.current years distributed computing actions toward turning into animportant worldview within the IT agency. extra undertakings desires to make use of allocated computing techniques for their groups, so distributed computing has become a giant studies place. In allotted computing cloud expert co-ops and customers are from various trust areas so records protection and protection are the sizable and primary troubles for far flung facts stockpiling. A blanketed patron compelled statistics get right of entry to manipulate system need to take delivery of earlier than cloud clients have the freedom to redistribute sensitive information to the cloud for capability. in this paper we have examined various get admission to control component for cloud protection

PHR in Cloud Environment Using Enhanced Attribute Based Encryption and Advanced Encryption Standard

2014 ◽  
Vol 573 ◽  
pp. 588-592
Author(s):  
T.B. Sivakumar ◽  
S. Geetha
Keyword(s):  
Public Health ◽  
Key Management ◽  
Personal Health Record ◽  
Personal Health ◽  
Health Record ◽  
Multiple Forms ◽  
Health Records ◽  
Attribute Based Encryption ◽  
And Performance ◽  
High Degree

Personal Health Record is internet based application that enables individuals to access and coordinates their womb-to-tomb health data. The patients have management over access to their own PHR. To attain security of non-public health records, we have a tendency to use the attribute based secret writing to write in code to inform before outsourcing it. Here we have a tendency to specialize in multiple forms of PHR owner situation and division of non-public health records users into multiple security domains that cut back key management complex for house owners and users. A high degree of patient’s privacy is secured. Our theme offer a personal health record owner full management of his/her information. In depth security and performance analysis shows that the projected theme is very economical.

scholarly journals Efficient Attribute-Based Secure Data Sharing with Hidden Policies and Traceability in Mobile Health Networks

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Changhee Hahn ◽  
Hyunsoo Kwon ◽  
Junbeom Hur
Keyword(s):  
Data Sharing ◽  
Mobile Health ◽  
Healthcare Providers ◽  
Personal Health ◽  
Sensitive Information ◽  
Health Records ◽  
Health Networks ◽  
Secure Data ◽  
Constrained Environments ◽  
Access Privileges

Mobile health (also written as mHealth) provisions the practice of public health supported by mobile devices. mHealth systems let patients and healthcare providers collect and share sensitive information, such as electronic and personal health records (EHRs) at any time, allowing more rapid convergence to optimal treatment. Key to achieving this is securely sharing data by providing enhanced access control and reliability. Typically, such sharing follows policies that depend on patient and physician preferences defined by a set of attributes. In mHealth systems, not only the data but also the policies for sharing it may be sensitive since they directly contain sensitive information which can reveal the underlying data protected by the policy. Also, since the policies usually incur linearly increasing communication costs, mHealth is inapplicable to resource-constrained environments. Lastly, access privileges may be publicly known to users, so a malicious user could illegally share his access privileges without the risk of being traced. In this paper, we propose an efficient attribute-based secure data sharing scheme in mHealth. The proposed scheme guarantees a hidden policy, constant-sized ciphertexts, and traces, with security analyses. The computation cost to the user is reduced by delegating approximately 50% of the decryption operations to the more powerful storage systems.

scholarly journals Simplified ciphertext-policy attribute-based encryption scheme with attribute level collusion resistance for cloud storage

2021 ◽  
Vol 2089 (1) ◽  
pp. 012010
Author(s):  
Naresh Vurukonda ◽  
Venkateshwarlu Velde ◽  
M. TrinathBasu ◽  
P. Tejasri
Keyword(s):  
Service Providers ◽  
Sensitive Information ◽  
Privacy Policy ◽  
Collusion Resistance ◽  
Cloud Data ◽  
Attribute Based Encryption ◽  
Cloud Server ◽  
Ciphertext Policy ◽  
And Control ◽  
Cloud Applications

Abstract The core objective of our paper is that to overcome the challenges of secure data sharing problem in cloud where users can access data if they acquire a certain set of attributes or credentials. At present, there is only one way for implementing such procedures is by employing a reliable server to mediate access control, store the data. The service providers have whole control over cloud applications, client’s data and hardware. However, if the data stored in the cloud server is conceded, then the data confidentiality will be compromised. With simplified CP-ABE data is confidential even though storage server is un trusted. Hence privacy of cloud data is enhanced by proposing a methodology that uses a privacy policy, encrypts the data based upon various group of attributes related to the user. The decryption of the data can be done only when his/her attributes match with the privacy policy. Simplified CP-ABE makes it easier to secure, broadcast and control the access of sensitive information, specifically across the cloud’s server and decrease collision resistance.

Differentially Private Medical Texts Generation Using Generative Neural Networks

2022 ◽  
Vol 3 (1) ◽  
pp. 1-27
Author(s):  
Md Momin Al Aziz ◽  
Tanbir Ahmed ◽  
Tasnia Faequa ◽  
Xiaoqian Jiang ◽  
Yiyu Yao ◽  
...  
Keyword(s):  
Data Science ◽  
Medical Information ◽  
Healthcare Providers ◽  
Well Being ◽  
Original Text ◽  
Sensitive Information ◽  
Classification Problems ◽  
Medical Texts ◽  
Health Records ◽  
Content Type

Technological advancements in data science have offered us affordable storage and efficient algorithms to query a large volume of data. Our health records are a significant part of this data, which is pivotal for healthcare providers and can be utilized in our well-being. The clinical note in electronic health records is one such category that collects a patient’s complete medical information during different timesteps of patient care available in the form of free-texts. Thus, these unstructured textual notes contain events from a patient’s admission to discharge, which can prove to be significant for future medical decisions. However, since these texts also contain sensitive information about the patient and the attending medical professionals, such notes cannot be shared publicly. This privacy issue has thwarted timely discoveries on this plethora of untapped information. Therefore, in this work, we intend to generate synthetic medical texts from a private or sanitized (de-identified) clinical text corpus and analyze their utility rigorously in different metrics and levels. Experimental results promote the applicability of our generated data as it achieves more than 80\% accuracy in different pragmatic classification problems and matches (or outperforms) the original text data.

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