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International Journal of Health... Mar 2021We introduce and study a recently proposed method for privacy-preserving distance computations which has received little attention in the scientific literature so far....
BACKGROUND
We introduce and study a recently proposed method for privacy-preserving distance computations which has received little attention in the scientific literature so far. The method, which is based on intersecting sets of randomly labeled grid points, is henceforth denoted as ISGP allows calculating the approximate distances between masked spatial data. Coordinates are replaced by sets of hash values. The method allows the computation of distances between locations L when the locations at different points in time t are not known simultaneously. The distance between [Formula: see text] and [Formula: see text] could be computed even when [Formula: see text] does not exist at [Formula: see text] and [Formula: see text] has been deleted at [Formula: see text]. An example would be patients from a medical data set and locations of later hospitalizations. ISGP is a new tool for privacy-preserving data handling of geo-referenced data sets in general. Furthermore, this technique can be used to include geographical identifiers as additional information for privacy-preserving record-linkage. To show that the technique can be implemented in most high-level programming languages with a few lines of code, a complete implementation within the statistical programming language R is given. The properties of the method are explored using simulations based on large-scale real-world data of hospitals ([Formula: see text]) and residential locations ([Formula: see text]). The method has already been used in a real-world application.
RESULTS
ISGP yields very accurate results. Our simulation study showed that-with appropriately chosen parameters - 99 % accuracy in the approximated distances is achieved.
CONCLUSION
We discussed a new method for privacy-preserving distance computations in microdata. The method is highly accurate, fast, has low computational burden, and does not require excessive storage.
Topics: Computer Simulation; Computer Systems; Humans; Privacy
PubMed: 33743719
DOI: 10.1186/s12942-021-00268-y -
Yonsei Medical Journal Sep 2022The purpose of this study is to present a legal system in which information is actively collected and utilized to monitor the location and health of self-quarantined... (Review)
Review
The purpose of this study is to present a legal system in which information is actively collected and utilized to monitor the location and health of self-quarantined persons through IT, to identify loopholes in the law and regulatory system in view of data protection and utilization, and to propose a legislative solution for those loopholes. In Korea, the Infectious Disease Control and Prevention Act ("the Prevention Act") regulates all matters related to the prevention and management of infectious diseases, including the use of information on self-quarantine apps. Article 42(2) of the Prevention Act states that local governments are authorized to collect the location and health information of a quarantined citizen; however, the law does not elaborate on how this information can be used and what other information can be used in combination with the collected information. Thus, the Personal Information Protection Act ("the Protection Act"), as a general privacy law, is applied supplementarily. However, since the Protection Act is very general and does not have accumulated cases, there is uncertainty about how governments can utilize the collected information. Therefore, it is necessary to consider a legislative solution that includes a direct and clear basis for the use of personal information collected under the Prevention Act in consideration of Korean privacy regulations.
Topics: Humans; Privacy; Quarantine; Republic of Korea
PubMed: 36031780
DOI: 10.3349/ymj.2022.63.9.806 -
Cold Spring Harbor Perspectives in... Mar 2015This review introduces patents and trade secrets, the two mechanisms that U.S. law provides inventors to protect their inventions. These mechanisms are mutually... (Review)
Review
This review introduces patents and trade secrets, the two mechanisms that U.S. law provides inventors to protect their inventions. These mechanisms are mutually exclusive: One demands disclosure and the other calls for concealment. Many biotechnology innovators opt for patents, which grant legal, time-limited monopolies to eligible inventions.To obtain a patent in the United States, an invention must be useful to the public and made or altered by the hand of man. It must then clear the hurdles of novelty and nonobviousness. If an invention can do that, obtaining a patent becomes a matter of form: Who qualifies as an inventor? Does the application demonstrate possession, stake a clear claim to the protection sought, and enable "ordinary" colleagues to replicate it? Has the inventor purposely withheld anything? This review addresses each of these hurdles as they apply to biotech inventions.
Topics: Biomedical Technology; Copyright; Humans; Intellectual Property; Patents as Topic; Privacy; United States
PubMed: 25818665
DOI: 10.1101/cshperspect.a020776 -
Sensors (Basel, Switzerland) Oct 2022Although many studies have been devoted to integrating blockchain into IoT device management, access control, data integrity, security, and privacy,...
Although many studies have been devoted to integrating blockchain into IoT device management, access control, data integrity, security, and privacy, blockchain-facilitated IoT communication is still much less studied. Blockchain has great potential in decentralizing and securing IoT communications. In this paper, we propose an innovative IoT service platform powered by the consortium blockchain technology. The proposed platform abstracts machine-to-machine (M2M) and human-to-machine (H2M) communications into services provided by IoT devices. Then, it materializes the data exchange of the IoT network through smart contracts and blockchain transactions. Additionally, we introduce the auxiliary storage layer to the proposed platform to address various off-chain data storage needs. Our proof-of-concept implementation was tested against various workloads and connection sizes under different block configurations to evaluate the platform's transaction throughput, latency, and hardware utilization. The experimental results demonstrate that our solution can maintain high performance with a throughput of approximately 800 reads per second (RPS), 50-80 transactions per second (TPS), and a latency of 50 ms-2 s under light to moderate workloads. Our extensive evaluation of the performance impact of batch size, batch timeout, and connection size also provides valuable insights into the optimization of blockchain configuration for achieving high performance.
Topics: Humans; Blockchain; Privacy; Information Storage and Retrieval
PubMed: 36365884
DOI: 10.3390/s22218186 -
Sensors (Basel, Switzerland) May 2023Location-based services (LBS) are widely used due to the rapid development of mobile devices and location technology. Users usually provide precise location information...
Location-based services (LBS) are widely used due to the rapid development of mobile devices and location technology. Users usually provide precise location information to LBS to access the corresponding services. However, this convenience comes with the risk of location privacy disclosure, which can infringe upon personal privacy and security. In this paper, a location privacy protection method based on differential privacy is proposed, which efficiently protects users' locations, without degrading the performance of LBS. First, a location-clustering (L-clustering) algorithm is proposed to divide the continuous locations into different clusters based on the distance and density relationships among multiple groups. Then, a differential privacy-based location privacy protection algorithm (DPLPA) is proposed to protect users' location privacy, where Laplace noise is added to the resident points and centroids within the cluster. The experimental results show that the DPLPA achieves a high level of data utility, with minimal time consumption, while effectively protecting the privacy of location information.
Topics: Privacy; Technology; Algorithms; Computers, Handheld; Cluster Analysis; Computer Security
PubMed: 37299946
DOI: 10.3390/s23115219 -
Applied Clinical Informatics Mar 2021The pace of technological change dwarfs the pace of social and policy change. This mismatch allows for individual harm from lack of recognition of changes in societal...
BACKGROUND
The pace of technological change dwarfs the pace of social and policy change. This mismatch allows for individual harm from lack of recognition of changes in societal context. The value of privacy has not kept pace with changes in technology over time; individuals seem to discount how loss of privacy can lead to directed personal harm.
OBJECTIVE
The authors examined individuals sharing personal data with mobile health applications (mHealth apps) and compared the current digital context to the historical context of harm. The authors make recommendations to informatics professionals to support consumers who wish to use mHealth apps in a manner that balances convenience with personal privacy to reduce the risk of harm.
METHODS
A literature search focused by a historical perspective of risk of harm was performed throughout the development of this paper. Two case studies highlight questions a consumer might ask to assess the risk of harm posed by mobile health applications.
RESULTS
A historical review provides the context for the collective human experience of harm. We then encapsulate current perceptions and views of privacy and list potential risks created by insufficient attention to privacy management.
DISCUSSION
The results provide a historical context for individuals to view the risk of harm and shed light on potential emotional, reputational, economic, and physical harms that can result from naïve use of mHealth apps. We formulate implications for clinical informaticists.
CONCLUSION
Concepts of both harm and privacy have changed substantially over the past 20 years. Technology provides methods to invade privacy and cause harm unimaginable a few decades ago. Only recently have the consequences become clearer. The current regulatory framework is extremely limited. Given the risks of harm and limited awareness, we call upon informatics professionals to support more privacy education and protections and increase mHealth transparency about data usage.
Topics: Humans; Informatics; Mobile Applications; Policy; Privacy; Telemedicine
PubMed: 33951741
DOI: 10.1055/s-0041-1727197 -
Journal of Environmental and Public... 2022In order to improve the security of the storage and scheduling of health privacy data inside and outside the university physical education class, a storage and...
In order to improve the security of the storage and scheduling of health privacy data inside and outside the university physical education class, a storage and scheduling method based on blockchain hybrid encryption is proposed. The distribution structure model of health privacy data blockchain inside and outside the university physical education class is established, arithmetic coding and quantitative feature analysis methods to schedule and adaptively control health privacy data blockchain inside and outside the university physical education class are adopted, public key coding configuration and vector quantization coding methods are combined to design encryption keys in the process of health privacy data transmission inside and outside the university physical education class, and blockchain hybrid encryption algorithm is adopted to design encryption keys for health privacy data inside and outside the university physical education class. The arithmetic coding is embedded in the encryption system, and the bit sequence output by the blockchain hybrid encryption is circularly shifted, so as to realize the encryption of health privacy data inside and outside the university physical education class and optimize the storage scheduling. The simulation results show that this method has good security encryption performance, strong antiattack ability, and balanced storage space allocation, which improves the security storage and transmission ability of health privacy data inside and outside the university physical education class.
Topics: Blockchain; Computer Security; Humans; Physical Education and Training; Privacy; Universities
PubMed: 36072498
DOI: 10.1155/2022/7506894 -
Computational Intelligence and... 2021Artificial Intelligence has been widely applied today, and the subsequent privacy leakage problems have also been paid attention to. Attacks such as model inference... (Review)
Review
Artificial Intelligence has been widely applied today, and the subsequent privacy leakage problems have also been paid attention to. Attacks such as model inference attacks on deep neural networks can easily extract user information from neural networks. Therefore, it is necessary to protect privacy in deep learning. Differential privacy, as a popular topic in privacy-preserving in recent years, which provides rigorous privacy guarantee, can also be used to preserve privacy in deep learning. Although many articles have proposed different methods to combine differential privacy and deep learning, there are no comprehensive papers to analyze and compare the differences and connections between these technologies. For this purpose, this paper is proposed to compare different differential private methods in deep learning. We comparatively analyze and classify several deep learning models under differential privacy. Meanwhile, we also pay attention to the application of differential privacy in Generative Adversarial Networks (GANs), comparing and analyzing these models. Finally, we summarize the application of differential privacy in deep neural networks.
Topics: Artificial Intelligence; Deep Learning; Neural Networks, Computer; Privacy
PubMed: 34745246
DOI: 10.1155/2021/4244040 -
Annals of Internal Medicine Jul 2021Technologic advancements and the evolving digital health landscape have offered innovative solutions to several of our health care system's issues as well as increased...
Technologic advancements and the evolving digital health landscape have offered innovative solutions to several of our health care system's issues as well as increased the number of digital interactions and type of personal health information that is generated and collected, both within and outside of traditional health care. This American College of Physicians' position paper discusses the state of privacy legislation and regulations, highlights existing gaps in health information privacy protections, and outlines policy principles and recommendations for the development of health information privacy and security protections that are comprehensive, transparent, understandable, adaptable, and enforceable. The principles and recommendations aim to improve on the privacy framework in which physicians have practiced for decades and expand similar privacy guardrails to entities not currently governed by privacy laws and regulations. The expanded privacy framework should protect personal health information from unauthorized, discriminatory, deceptive, or harmful uses and align with the principles of medical ethics, respect individual rights, and support the culture of trust necessary to maintain and improve care delivery.
Topics: Computer Security; Digital Technology; Electronic Health Records; Health Records, Personal; Humans; Privacy; United States
PubMed: 33900797
DOI: 10.7326/M20-7639 -
Medicine, Health Care, and Philosophy Mar 2023AAL encompasses smart home technologies that are installed in the personal living environment in order to support older, disabled, as well as chronically ill people with...
AAL encompasses smart home technologies that are installed in the personal living environment in order to support older, disabled, as well as chronically ill people with the goal of delaying or reducing their need for nursing care in a care facility. Artificial intelligence (AI) is seen as an important tool for assisting the target group in their daily lives. A literature search and qualitative content analysis of 255 articles from computer science and engineering was conducted to explore the usage of ethical concepts. From an ethical point of view, the concept of independence and self-determination on the one hand and the possible loss of privacy on the other hand are widely discussed in the context of AAL. These concepts are adopted by the technical discourse in the sense that independence, self-determination and privacy are recognized as important values. Nevertheless, our research shows that these concepts have different usages and meanings in the ethical and the technical discourses. In the paper, we aim to map the different meanings of independence, self-determination and privacy as they can be found in the context of technological research on AI-based AAL systems. It investigates the interpretation of these ethical and social concepts which technicians try to build into AAL systems. In a second step, these interpretations are contextualized with concepts from the ethical discourse on AI-based assistive technologies.
Topics: Humans; Privacy; Artificial Intelligence; Self-Help Devices; Disabled Persons; Technology
PubMed: 36348209
DOI: 10.1007/s11019-022-10126-8