An Efficient Watermarking Based Matrix Manipulation and Optimization Based Cryptographic Method for Privacy Preservation in Biomedical Data

2021 ◽  
Vol 11 (12) ◽  
pp. 2928-2936
Author(s):  
S. Vairaprakash ◽  
A. Shenbagavalli ◽  
S. Rajagopal
Keyword(s):  
Privacy Preservation ◽  
Fitness Function ◽  
Health Care Systems ◽  
Automatic Device ◽  
Expert Advice ◽  
Modern World ◽  
Biomedical Data ◽  
Patient Privacy ◽  
Secret Key ◽  
Biomedical Images

The biomedical processing of images is an important aspect of the modern medicine field and has an immense influence on the modern world. Automatic device assisted systems are immensely useful in order to diagnose biomedical images easily, accurately and effectively. Remote health care systems allow medical professionals and patients to work from different locations. In addition, expert advice on a patient can be received within a prescribed period of time from a specialist in a foreign country or in a remote area. Digital biomedical images must be transmitted over the network in remote healthcare systems. But the delivery of the biomedical goods entails many security challenges. Patient privacy must be protected by ensuring that images are secure from unwanted access. Furthermore, it must be effectively maintained so that nothing will affect the content of biomedical images. In certain instances, data manipulation can yield dramatic effects. A biomedical image safety method was suggested in this work. The suggested method will initially be used to construct a binary pixel encoding matrix and then to adjust matrix with the use of decimation mutation DNA watermarking principle. Afterwards to defend the sub keys couple privacy which was considered over the logical uplift utilization of tent maps and purpose. As acknowledged by chaotic (C-function) development, the security was investigated similar to transmission in addition to uncertainty. Depending on the preliminary circumstances, various numbers of random were generated intended for every map as of chaotic maps. An algorithm of Multi scale grasshopper optimization resource with correlation coefficient fitness function and PSNR was projected for choosing the optimal public key and secret key of system over random numbers. For choosing the validation process of optimization is to formulate novel model more relative stable to the conventional approach. In conclusion, the considered suggested findings were contrasted with current approaches protection that was appear to be successful extremely.

scholarly journals Evaluation of Privacy Risks of Patients’ Data in China: Case Study

10.2196/13046 ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. e13046 ◽  
Author(s):  
Mengchun Gong ◽  
Shuang Wang ◽  
Lezi Wang ◽  
Chao Liu ◽  
Jianyang Wang ◽  
...  
Keyword(s):  
Health Care ◽  
Data Sharing ◽  
Data Privacy ◽  
Patient Data ◽  
Chinese Patients ◽  
Biomedical Data ◽  
Safe Harbor ◽  
Patient Privacy ◽  
Privacy Risk ◽  
Privacy Risks

Background Patient privacy is a ubiquitous problem around the world. Many existing studies have demonstrated the potential privacy risks associated with sharing of biomedical data. Owing to the increasing need for data sharing and analysis, health care data privacy is drawing more attention. However, to better protect biomedical data privacy, it is essential to assess the privacy risk in the first place. Objective In China, there is no clear regulation for health systems to deidentify data. It is also not known whether a mechanism such as the Health Insurance Portability and Accountability Act (HIPAA) safe harbor policy will achieve sufficient protection. This study aimed to conduct a pilot study using patient data from Chinese hospitals to understand and quantify the privacy risks of Chinese patients. Methods We used g-distinct analysis to evaluate the reidentification risks with regard to the HIPAA safe harbor approach when applied to Chinese patients’ data. More specifically, we estimated the risks based on the HIPAA safe harbor and limited dataset policies by assuming an attacker has background knowledge of the patient from the public domain. Results The experiments were conducted on 0.83 million patients (with data field of date of birth, gender, and surrogate ZIP codes generated based on home address) across 33 provincial-level administrative divisions in China. Under the Limited Dataset policy, 19.58% (163,262/833,235) of the population could be uniquely identifiable under the g-distinct metric (ie, 1-distinct). In contrast, the Safe Harbor policy is able to significantly reduce privacy risk, where only 0.072% (601/833,235) of individuals are uniquely identifiable, and the majority of the population is 3000 indistinguishable (ie the population is expected to share common attributes with 3000 or less people). Conclusions Through the experiments based on real-world patient data, this work illustrates that the results of g-distinct analysis about Chinese patient privacy risk are similar to those from a previous US study, in which data from different organizations/regions might be vulnerable to different reidentification risks under different policies. This work provides reference to Chinese health care entities for estimating patients’ privacy risk during data sharing, which laid the foundation of privacy risk study about Chinese patients’ data in the future.

scholarly journals A Secure and Privacy-Aware Smart Health System with Secret Key Leakage Resilience

2018 ◽  
Vol 2018 ◽  
pp. 1-13 ◽  
Author(s):  
Yinghui Zhang ◽  
Pengzhen Lang ◽  
Dong Zheng ◽  
Menglei Yang ◽  
Rui Guo
Keyword(s):  
Health System ◽  
Data Security ◽  
Medical Information ◽  
Patient Privacy ◽  
Secret Key ◽  
Diffie Hellman ◽  
Cryptographic Primitive ◽  
Leakage Resilient ◽  
Smart Health ◽  
Health Data Security

With the development of the smart health (s-health), data security and patient privacy are becoming more and more important. However, some traditional cryptographic schemes can not guarantee data security and patient privacy under various forms of leakage attacks. To prevent the adversary from capturing the part of private keys by leakage attacks, we propose a secure leakage-resilient s-health system which realizes privacy protection and the safe transmission of medical information in the case of leakage attacks. The key technique is a promising public key cryptographic primitive called leakage-resilient anonymous Hierarchical Identity-Based Encryption. Our construction is proved to be secure against chosen plaintext attacks in the standard model under the Diffie-Hellman exponent assumption and decisional linear assumption. We also blind the public parameters and ciphertexts by using double exponent technique to achieve the recipient anonymity. Finally, the performance analysis shows the practicability of our scheme, and the leakage rate of the private key approximates to 1/6.

scholarly journals Cloud-Assisted Privacy-Preserving Method for Healthcare Using Adaptive Fractional Brain Storm Integrated Whale Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
S. Thanga Revathi ◽  
A. Gayathri ◽  
J. Kalaivani ◽  
Mary Subaja Christo ◽  
Danilo Pelusi ◽  
...  
Keyword(s):  
Optimization Algorithm ◽  
Fitness Function ◽  
Data Retrieval ◽  
Medical Data ◽  
Whale Optimization Algorithm ◽  
Experimental Result ◽  
Secret Key ◽  
Healthcare Data ◽  
Maximum Utility ◽  
Whale Optimization

The security of medical data in the cloud is the key consideration of cloud customers. While publishing the medical data, the cloud distributor may suffer from data leakages and attacks such that the data may leak. In order to resolve this, this article devises the developed Adaptive Fractional Brain Storm Integrated Whale Optimization Algorithm (AFBS_WOA), which is the hybridization of Adaptive Fractional Brain Storm Optimization (AFBSO) and Whale Optimization algorithm (WOA). The developed AFBS_WOA algorithm generates the key matrix coefficient for retrieving the perturbed database in order to preserve the privacy of healthcare data in the cloud. The developed AFBS-WOA scheme utilized the fitness function involving utility and privacy measures for calculating the secret key. Here, the privacy-preserved database is obtained by multiplying the input database with a key matrix based on developed AFBS-WOA using the Tracy–Singh product. For data retrieval, the secret key is shared with the service provider in order to retrieve the database, and then the data are accessed. Moreover, the experimental result demonstrates that the developed AFBS_WOA model attained the maximum utility and privacy measure of 0.1872 and 0.8755 using the Hungarian dataset.

scholarly journals dSNE: a visualization approach for use with decentralized data

2019 ◽  
Author(s):  
D. K. Saha ◽  
V. D. Calhoun ◽  
Y. Du ◽  
Z. Fu ◽  
S. R. Panta ◽  
...  
Keyword(s):  
Quality Control ◽  
Large Scale ◽  
Privacy Preservation ◽  
Vital Role ◽  
Biomedical Data ◽  
Brain Images ◽  
Privacy Concerns ◽  
Quality Control Tool ◽  
Two Samples ◽  
The Individual

AbstractVisualization of high dimensional large-scale datasets via an embedding into a 2D map is a powerful exploration tool for assessing latent structure in the data and detecting outliers. It plays a vital role in neuroimaging field because sometimes it is the only way to perform quality control of large dataset. There are many methods developed to perform this task but most of them rely on the assumption that all samples are locally available for the computation. Specifically, one needs access to all the samples in order to compute the distance directly between all pairs of points to measure the similarity. But all pairs of samples may not be available locally always from local sites for various reasons (e.g. privacy concerns for rare disease data, institutional or IRB policies). This is quite common for biomedical data, e.g. neuroimaging and genetic, where privacy-preservation is a major concern. In this scenario, a quality control tool that visualizes decentralized dataset in its entirety via global aggregation of local computations is especially important as it would allow screening of samples that cannot be evaluated otherwise. We introduced an algorithm to solve this problem: decentralized data stochastic neighbor embedding (dSNE). In our approach, data samples (i.e. brain images) located at different sites are simultaneously mapped into the same space according to their similarities. Yet, the data never leaves the individual sites and no pairwise metric is ever directly computed between any two samples not collocated. Based on the Modified National Institute of Standards and Technology database (MNIST) and the Columbia Object Image Library (COIL-20) dataset we introduce metrics for measuring the embedding quality and use them to compare dSNE to its centralized counterpart. We also apply dSNE to various multi-site neuroimaging datasets and show promising results which highlight the potential of our decentralized visualization approach.

Security Evaluation Methods in Trust Infrastructure Based on Engineering and Economics

Impact ◽  
2019 ◽  
Vol 2019 (10) ◽  
pp. 24-26
Author(s):  
Kanta Matsuura
Keyword(s):  
Modern World ◽  
Security Evaluation ◽  
Secret Key ◽  
Scientific Rigor ◽  
Secure Systems ◽  
The Public ◽  
Online Purchases ◽  
Phone Calls ◽  
Cryptographic System ◽  
The University

The modern world runs on data. It is one of the most valuable commodities and many of our day to day activities are based on generating or using this data. The convenience of our world, in which a single device brings us internet searches, shopping lists, online purchases, texts and phone calls is designed to create, store and use data to make life easier and more and more of our daily activities will be conducted online despite security concerns. For example, online purchasing and banking require guarantees that customers data and identities are verifiable and secure. The act of voting is also now moving to being completed online. While this would surely encourage more people to vote by making the process available on your smartphone, the security and integrity of the system is a concern. Is the system hackable? Can it be shutdown by malicious actors, causing chaos on voting day? How can we be sure that the person casting the vote online is in fact that person or that they are not being coerced to cast a certain ballot. These are just a few examples of the breadth of the information security field and the foresight required to build secure systems. Kanta Matsuura, who is a Professor at the Institute of Industrial Science in the University of Tokyo, has been working in this area since the early 2000s. For him, these are issues that the public needs to understand so they can trust in the security tools being developed, such as cryptography and blockchain technologies. 'Traditionally in cryptography, there is a well-known principle proposed by Auguste Kerckhoffs that says a cryptographic system should be secure even if everything about the system, except the secret key, is public knowledge and available to attackers,' says Matsuura. 'To build such a system requires a careful evaluation of these infrastructures before they are designed, known as security by design.' Matsuura therefore believes that stakeholders be well informed regarding the methods used in the construction of the system and the methods used in the security evaluation of the system. 'This introduces scientific rigor to the discipline, and contributes to real-world activities such as standardisation, product validation, risk communication, and so on,' he says

Amendments to the Constitution of the Russian Federation: Dictated Necessity and Consequences in the Conditions of the Modern World

2021 ◽  
Author(s):  
V.V. Chuksina ◽  
◽  
K.A. Mirvoda ◽  
Keyword(s):  
Health Care ◽  
Medical Care ◽  
Russian Federation ◽  
Local Governments ◽  
Health Care Systems ◽  
Modern World ◽  
Depth Analysis ◽  
Care Systems ◽  
The Russian Federation ◽  
The Impact

The subject of this article is Law of the Russian Federation on Amendments to the Constitution of the Russian Federation (14.03.2020 No. 1-Federal Constitutional Law) «On improving the regulation of certain issues of the public power organization and functioning», namely, aspects of «coordination of health care» and «protection of the family, motherhood and childhood». The authors analyzed the issues of the medical care provision centralization, the impact of these amendments on the legal capacity of citizens. For a more in-depth analysis, the experience of foreign countries (Canada and Germany) was used. Despite the fact that the health care systems of the countries cited as an example differ in their essence and organization, nevertheless, they influence the formation of the availability of medicine for the population. As a result of the study of this experience, it was concluded that the delegation of freedom in the provision of medical care to lower levels of government allows to provide to the population affordable and high-quality medical care. It is noted that at present it is necessary to review the degree of participation of local governments in ensuring the availability of medical care in accordance with the federal law.

A Review of Different Techniques for Biomedical Data Security

2021 ◽  
pp. 1179-1202
Author(s):  
Harminder Kaur ◽  
Sharvan Kumar Pahuja
Keyword(s):  
Healthcare Providers ◽  
Physiological Data ◽  
Main Concern ◽  
Biomedical Data ◽  
Patient Privacy ◽  
Privacy Concerns ◽  
Security Issues ◽  
The People ◽  
Mental Abilities ◽  
Restricted Mobility

The aging population is vulnerable to various illnesses and health conditions because with increase in age the people suffer from chronic disease. Quite often, they are partially handicapped due to their restricted mobility and their reduced mental abilities. To resolve these problems, health monitoring systems are designed for real-time monitoring of patients. WBAN use medical sensors for acquiring patient physiological data with wireless technologies to send data to healthcare providers. Due to wireless transmission, the chances of attacking and occurring security issues in the data are more. So, the security of the system is the main concern because the system consists of patient privacy concerns. Due to these reasons there is need of designing security algorithms to prevent data from being stolen by attackers. The aim of this chapter is to present a review of different attacks that occurred during transmission of data and security issues related to data. The chapter also describes different algorithms to prevent data from being stolen through various attacks and security issues.

Exponential Ant-Lion Rider Optimization for Privacy Preservation in Cloud Computing

2021 ◽  
pp. 1-19
Author(s):  
Nagaraju Pamarthi ◽  
N. Nagamalleswara Rao
Keyword(s):  
Cloud Computing ◽  
Optimization Algorithm ◽  
Privacy Preservation ◽  
Fitness Function ◽  
Information Loss ◽  
Superior Performance ◽  
Data Matrix ◽  
Sensitive Information ◽  
Bilinear Map ◽  
Ant Lion

The innovative trend of cloud computing is outsourcing data to the cloud servers by individuals or enterprises. Recently, various techniques are devised for facilitating privacy protection on untrusted cloud platforms. However, the classical privacy-preserving techniques failed to prevent leakage and cause huge information loss. This paper devises a novel methodology, namely the Exponential-Ant-lion Rider optimization algorithm based bilinear map coefficient Generation (Exponential-AROA based BMCG) method for privacy preservation in cloud infrastructure. The proposed Exponential-AROA is devised by integrating Exponential weighted moving average (EWMA), Ant Lion optimizer (ALO), and Rider optimization algorithm (ROA). The input data is fed to the privacy preservation process wherein the data matrix, and bilinear map coefficient Generation (BMCG) coefficient are multiplied through Hilbert space-based tensor product. Here, the bilinear map coefficient is obtained by multiplying the original data matrix and with modified elliptical curve cryptography (MECC) encryption to maintain data security. The bilinear map coefficient is used to handle both the utility and the sensitive information. Hence, an optimization-driven algorithm is utilized to evaluate the optimal bilinear map coefficient. Here, the fitness function is newly devised considering privacy and utility. The proposed Exponential-AROA based BMCG provided superior performance with maximal accuracy of 94.024%, maximal fitness of 1, and minimal Information loss of 5.977%.

Body Sensor Network Processing Mechanism for Micro-Data Security Publishing

2014 ◽  
Vol 1049-1050 ◽  
pp. 1536-1539
Author(s):  
Na Li
Keyword(s):  
Sensor Network ◽  
Data Security ◽  
Privacy Preservation ◽  
Data Publishing ◽  
Challenging Problem ◽  
Patient Privacy ◽  
Micro Data ◽  
Body Sensor Network ◽  
Resources Sharing ◽  
Processing Mechanism

Individuals’ privacy protection when publishing data for research has recently put great attention on data mining and information resources sharing fields. Privacy preservation is an important and challenging problem in micro-data publishing. This paper aimed to find an available directly way protect patient privacy. Processing numeric values which got from body sensor network (BSN). Firstly, we analyze the characteristics of medical data which collected from BSN, and then the records will be grouped according to the Quasi-identifier. The last step is to inspect the diversity of sensitive attributes.

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