Ensuring privacy and security of genomic data and functionalities

2019 ◽  
Vol 21 (2) ◽  
pp. 511-526 ◽  
Author(s):  
Abukari Mohammed Yakubu ◽  
Yi-Ping Phoebe Chen
Keyword(s):  
Association Studies ◽  
Diagnostic Testing ◽  
Healthcare Delivery ◽  
Genomic Data ◽  
Security And Privacy ◽  
Genome Wide Association Studies ◽  
Privacy And Security ◽  
Security Issues ◽  
Genomic Privacy ◽  
Privacy Problem

Abstract In recent times, the reduced cost of DNA sequencing has resulted in a plethora of genomic data that is being used to advance biomedical research and improve clinical procedures and healthcare delivery. These advances are revolutionizing areas in genome-wide association studies (GWASs), diagnostic testing, personalized medicine and drug discovery. This, however, comes with security and privacy challenges as the human genome is sensitive in nature and uniquely identifies an individual. In this article, we discuss the genome privacy problem and review relevant privacy attacks, classified into identity tracing, attribute disclosure and completion attacks, which have been used to breach the privacy of an individual. We then classify state-of-the-art genomic privacy-preserving solutions based on their application and computational domains (genomic aggregation, GWASs and statistical analysis, sequence comparison and genetic testing) that have been proposed to mitigate these attacks and compare them in terms of their underlining cryptographic primitives, security goals and complexities—computation and transmission overheads. Finally, we identify and discuss the open issues, research challenges and future directions in the field of genomic privacy. We believe this article will provide researchers with the current trends and insights on the importance and challenges of privacy and security issues in the area of genomics.

A review on Privacy-Preserving Data Preprocessing

2020 ◽  
pp. 16-30
Author(s):  
Mukesh Soni ◽  
◽  
◽  
◽  
YashKumar Barot ◽  
...  
Keyword(s):  
Health Care ◽  
Information Security ◽  
Social Insurance ◽  
Disease Outbreaks ◽  
Security And Privacy ◽  
Health Care Information ◽  
Privacy And Security ◽  
Healthcare Data ◽  
Security Issues ◽  
Care Information

Health care information has great potential for improving the health care system and also providing fast and accurate outcomes for patients, predicting disease outbreaks, gaining valuable information for prediction in future, preventing such diseases, reducing healthcare costs, and improving overall health. In any case, deciding the genuine utilization of information while saving the patient's identity protection is an overwhelming task. Regardless of the amount of medical data it can help advance clinical science and it is essential to the accomplishment of all medicinal services associations, at the end information security is vital. To guarantee safe and solid information security and cloud-based conditions, It is critical to consider the constraints of existing arrangements and systems for the social insurance of information security and assurance. Here we talk about the security and privacy challenges of high-quality important data as it is used mainly by the healthcare structure and similar industry to examine how privacy and security issues occur when there is a large amount of healthcare information to protect from all possible threats. We will discuss ways that these can be addressed. The main focus will be on recently analyzed and optimized methods based on anonymity and encryption, and we will compare their strengths and limitations, and this chapter closes at last the privacy and security recommendations for best practices for privacy of preprocessing healthcare data.

scholarly journals Privacy and Security Issues in Online Social Networks

2018 ◽  
Vol 10 (12) ◽  
pp. 114 ◽  
Author(s):  
Shaukat Ali ◽  
Naveed Islam ◽  
Azhar Rauf ◽  
Ikram Din ◽  
Mohsen Guizani ◽  
...  
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Virtual Communities ◽  
Service Providers ◽  
Security And Privacy ◽  
Security Issue ◽  
Sensitive Data ◽  
Privacy And Security ◽  
Security Issues ◽  
Social Sphere

The advent of online social networks (OSN) has transformed a common passive reader into a content contributor. It has allowed users to share information and exchange opinions, and also express themselves in online virtual communities to interact with other users of similar interests. However, OSN have turned the social sphere of users into the commercial sphere. This should create a privacy and security issue for OSN users. OSN service providers collect the private and sensitive data of their customers that can be misused by data collectors, third parties, or by unauthorized users. In this paper, common security and privacy issues are explained along with recommendations to OSN users to protect themselves from these issues whenever they use social media.

scholarly journals Data safe havens to combine health and genomic data: benefits and challenges

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Kerina H Jones ◽  
Arron S Lacey ◽  
Brian L Perkins ◽  
Mark I Rees
Keyword(s):  
Association Studies ◽  
Genomic Data ◽  
Population Level ◽  
Data Availability ◽  
Genome Wide Association Studies ◽  
Related Data ◽  
Research Areas ◽  
Individual Privacy ◽  
Access Controls ◽  
Health Related

ABSTRACTObjectivesData safe havens can bring together and combine a rich array of anonymised person-based data for research and policy evaluation within a secure setting. To date, the majority of available datasets have been structured micro-data derived from routine health-related records. Possibilities are opening up for the greater reuse of genomic data such as Genome Wide Association studies (GWAS) and Whole Exome/Genome Sequencing (WES or WGS). However, there are considerable challenges to be addressed if the benefits of using these data in combination with health-related data are to be realized safely. ApproachWe explore the benefits and challenges of using genomic datasets with health-related data, and using the Secure Anonymised Information Linkage (SAIL) system as a case study, the implications and way forward for Data Safe Havens in seeking to incorporate genomic data for use with health-related data. ResultsThe benefits of using GWAS, WES and WGS data in conjunction with health-related data include the potential to explore genetics at a population level and open up novel research areas. These include the ability to increasingly stratify and personalize how medical indications are detected and treated through precision medicine by understanding rare conditions and adding socioeconomic and environmental context to genomic data. Among the challenges are: data availability, computing capacity, technical solutions, legal and regulatory frameworks, public perceptions, individual privacy and organizational risk. Many of the challenges within these areas are common to person-based data in general, and often Data Safe Havens have been designed to address these. But there are also aspects of these challenges, and other challenges, specific to genomic data. These include issues due to the unknown clinical significance of genomic information now or in the future, with corresponding risks for privacy and impact on individuals. ConclusionGenomic data sets contain vast amounts of valuable information, some of which is currently undefined, but which may have direct bearing on individual health at some point. The use of these data in combination with health-related data has the potential to bring great benefits, better clinical trial stratification, epidemiology project design and clinical improvements. It is, therefore, essential that such data are surrounded by a properly-designed, robust governance framework including technical and procedural access controls that enable the data to be used safely.

IoT in Healthcare

2020 ◽  
pp. 1-22
Author(s):  
V. Jeevika Tharini ◽  
S. Vijayarani
Keyword(s):  
Health Sector ◽  
Information Privacy ◽  
Security And Privacy ◽  
Healthcare Industry ◽  
Security Attacks ◽  
Privacy And Security ◽  
Privacy Concerns ◽  
Security Issues ◽  
Iot Devices ◽  
Individual Information

One of the best-known features of IoT is automation. Because of this, IoT is a much-needed field for many applications, namely emergency and healthcare domains. IoT has made many revolutionary changes in the healthcare industry. IoT paves the way to numerous advancements for healthcare. The possibilities of IoT have reached their peak in the commercial industry and health sector. In recent years, serious concerns have been raised over the control and access of one's individual information. Privacy and security of the IoT devices can be compromised by intruders. Apart from the numerous benefits of IoTs, there are several security and privacy concerns to consider. A brief overview of different kinds of security attacks, solution for the attacks, privacy and security issues are discussed in this chapter.

Study and Survey on Blockchain Privacy and Security Issues

2021 ◽  
pp. 169-191
Author(s):  
Sourav Banerjee ◽  
Debashis Das ◽  
Manju Biswas ◽  
Utpal Biswas
Keyword(s):  
Data Storage ◽  
Security And Privacy ◽  
Sensitive Information ◽  
Privacy And Security ◽  
Unauthorized Access ◽  
Security Issues ◽  
Blockchain Technology ◽  
Targeted Attacks ◽  
Wide Range ◽  
Financial Transactions

Blockchain-based technology is becoming increasingly popular and is now used to solve a wide range of tasks. And it's not all about cryptocurrencies. Even though it's based on secure technology, a blockchain needs protection as well. The risks of exploits, targeted attacks, or unauthorized access can be mitigated by the instant incident response and system recovery. Blockchain technology relies on a ledger to keep track of all financial transactions. Ordinarily, this kind of master ledger would be a glaring point of vulnerability. Another tenet of security is the chain itself. Configuration flaws, as well as insecure data storage and transfers, may cause leaks of sensitive information. This is even more dangerous when there are centralized components within the platform. In this chapter, the authors will demonstrate where the disadvantages of security and privacy in blockchain are currently and discuss how blockchain technology can improve these disadvantages and outlines the requirements for future solution.

scholarly journals Mobile Government Applications Based on Security and Privacy: A Literature Review

2018 ◽  
Vol 7 (4.1) ◽  
pp. 51
Author(s):  
Ala'a Saeb Al-Sherideh ◽  
Roesnita Ismail ◽  
Fauziah Abdul Wahid ◽  
Norasikin Fabil ◽  
Waidah Ismail
Keyword(s):  
Literature Review ◽  
Mobile Applications ◽  
Public Services ◽  
Security Requirements ◽  
Security And Privacy ◽  
Privacy And Security ◽  
The Public ◽  
Privacy Requirements ◽  
Security Issues ◽  
The Government

Mobile applications available in anytime and from anywhere. The utilizing of mobile governmental applications is significant to reduce the efforts and time that are required to accomplish the public services by citizens. The main challenges that face the acceptance and adoption of mobile governmental applications are the privacy and security issues. The users, who do not trust the security of mobile governmental applications, may reject the use of these applications which discourages the government to adopt the mobile services. This study focuses in investigating the security and privacy requirements of mobile government applications. Many related works are reviewed and discussed to understand the important security requirements of mobile government applications. The main results indicate that effective privacy and security of mobile government applications should be assured so as to enhance the level of adopting and using these applications. The security requirements involve many considerations such as the hardware characteristics, software characteristics, and communication characteristics. This article mainly gives better understanding of security requirements of mobile government applications.   

A Comprehensive Survey on Privacy and Security Issues in Cloud Computing, Internet of Things and Cloud of Things

2019 ◽  
Vol 10 (3) ◽  
pp. 32-44
Author(s):  
Syrine Sahmim Ep Guerbouj ◽  
Hamza Gharsellaoui ◽  
Sadok Bouamama
Keyword(s):  
Risk Factors ◽  
Cloud Computing ◽  
Internet Of Things ◽  
Journal Article ◽  
Security And Privacy ◽  
Future Trends ◽  
Privacy And Security ◽  
Security Issues ◽  
Existing Problems ◽  
Comprehensive Survey

This journal article deals with the most important existing problems of security and privacy of the Cloud Computing (CC), Internet of Things (IoT) and Cloud of Things (CoT) concepts especially confidentiality issues. With the evolution of ubiquitous computing, everything is connected everywhere, therefore these concepts have been widely studied in the literature. However, due to the systems complexity and the difficulty to control each access attempt, intrusions and vulnerabilities will be more recurrent. To tackle this issue, researchers have been focused on various approaches enforcing security and privacy. In the present article, risk factors and solutions regarding these technologies are reviewed then current and future trends are discussed.

A Review of Security Challenges in Cloud Storage of Big Data

2019 ◽  
pp. 1440-1459
Author(s):  
Sara Usmani ◽  
Faiza Rehman ◽  
Sajid Umair ◽  
Safdar Abbas Khan
Keyword(s):  
Information Technology ◽  
Cloud Computing ◽  
Big Data ◽  
Data Storage ◽  
Cloud Storage ◽  
Personal Data ◽  
Security And Privacy ◽  
Privacy And Security ◽  
Security Issues ◽  
The People

The novel advances in the field of Information Technology presented the people pleasure, luxuries and ease. One of the latest expansions in the Information Technology (IT) industry is Cloud Computing, a technology that uses the internet for storage and access of data. It is also known as on-demand computing. The end user can access personal data and applications anywhere any time with a device having internet. Cloud Computing has gained an enormous attention but it results in the issues of data security and privacy as the data is scattered on different machines in different places across the globe which is a serious threat to the technology. It has many advantages like flexibility, efficiency and scalability but many of the companies are hesitant to invest in it due to privacy concerns. In this chapter, the objective is to review the privacy and security issues in cloud storage of Big Data and to enhance the security in cloud environment so that end users can enjoy a trustworthy and reliable data storage and access.

scholarly journals Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration

2020 ◽  
Vol 46 (1) ◽  
pp. 86-97 ◽  
Author(s):  
Timothy Reynolds ◽  
Emma C. Johnson ◽  
Spencer B. Huggett ◽  
Jason A. Bubier ◽  
Rohan H. C. Palmer ◽  
...  
Keyword(s):  
Data Integration ◽  
Genetic Variants ◽  
Association Studies ◽  
Model Organism ◽  
Genomic Data ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Behavioral Traits ◽  
Genome Wide ◽  
Advanced Analysis

AbstractGenome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

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