• Title/Summary/Keyword: genetic privacy

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Ethical Considerations in Genomic Cohort Study (유전체 코호트 연구의 윤리적 고려 사항)

  • Choi, Eun-Kyung;Kim, Ock-Joo
    • Journal of Preventive Medicine and Public Health
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    • v.40 no.2
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    • pp.122-129
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    • 2007
  • During the last decade, genomic cohort study has been developed in many countries by linking health data and genetic data in stored samples. Genomic cohort study is expected to find key genetic components that contribute to common diseases, thereby promising great advance in genome medicine. While many countries endeavor to build biobank systems, biobank-based genome research has raised important ethical concerns including genetic privacy, confidentiality, discrimination, and informed consent. Informed consent for biobank poses an important question: whether true informed consent is possible in population-based genomic cohort research where the nature of future studies is unforeseeable when consent is obtained. Due to the sensitive character of genetic information, protecting privacy and keeping confidentiality become important topics. To minimize ethical problems and achieve scientific goals to its maximum degree, each country strives to build population-based genomic cohort research project, by organizing public consultation, trying public and expert consensus in research, and providing safeguards to protect privacy and confidentiality.

A Differential Privacy Approach to Preserve GWAS Data Sharing based on A Game Theoretic Perspective

  • Yan, Jun;Han, Ziwei;Zhou, Yihui;Lu, Laifeng
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.16 no.3
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    • pp.1028-1046
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    • 2022
  • Genome-wide association studies (GWAS) aim to find the significant genetic variants for common complex disease. However, genotype data has privacy information such as disease status and identity, which make data sharing and research difficult. Differential privacy is widely used in the privacy protection of data sharing. The current differential privacy approach in GWAS pays no attention to raw data but to statistical data, and doesn't achieve equilibrium between utility and privacy, so that data sharing is hindered and it hampers the development of genomics. To share data more securely, we propose a differential privacy preserving approach of data sharing for GWAS, and achieve the equilibrium between privacy and data utility. Firstly, a reasonable disturbance interval for the genotype is calculated based on the expected utility. Secondly, based on the interval, we get the Nash equilibrium point between utility and privacy. Finally, based on the equilibrium point, the original genotype matrix is perturbed with differential privacy, and the corresponding random genotype matrix is obtained. We theoretically and experimentally show that the method satisfies expected privacy protection and utility. This method provides engineering guidance for protecting GWAS data privacy.

A new approach for k-anonymity based on tabu search and genetic algorithm

  • Run, Cui;Kim, Hyoung-Joong;Lee, Dal-Ho
    • Journal of The Institute of Information and Telecommunication Facilities Engineering
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    • v.10 no.4
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    • pp.128-134
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    • 2011
  • Note that k-anonymity algorithm has been widely discussed in the area of privacy protection. In this paper, a new search algorithm to achieve k-anonymity for database application is introduced. A lattice is introduced to form a solution space for a k-anonymity problem and then a hybrid search method composed of tabu search and genetic algorithm is proposed. In this algorithm, the tabu search plays the role of mutation in the genetic algorithm. The hybrid method with independent tabu search and genetic algorithm is compared, and the hybrid approach performs the best in average case.

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Similarity measurement based on Min-Hash for Preserving Privacy

  • Cha, Hyun-Jong;Yang, Ho-Kyung;Song, You-Jin
    • International Journal of Advanced Culture Technology
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    • v.10 no.2
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    • pp.240-245
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    • 2022
  • Because of the importance of the information, encryption algorithms are heavily used. Raw data is encrypted and secure, but problems arise when the key for decryption is exposed. In particular, large-scale Internet sites such as Facebook and Amazon suffer serious damage when user data is exposed. Recently, research into a new fourth-generation encryption technology that can protect user-related data without the use of a key required for encryption is attracting attention. Also, data clustering technology using encryption is attracting attention. In this paper, we try to reduce key exposure by using homomorphic encryption. In addition, we want to maintain privacy through similarity measurement. Additionally, holistic similarity measurements are time-consuming and expensive as the data size and scope increases. Therefore, Min-Hash has been studied to efficiently estimate the similarity between two signatures Methods of measuring similarity that have been studied in the past are time-consuming and expensive as the size and area of data increases. However, Min-Hash allowed us to efficiently infer the similarity between the two sets. Min-Hash is widely used for anti-plagiarism, graph and image analysis, and genetic analysis. Therefore, this paper reports privacy using homomorphic encryption and presents a model for efficient similarity measurement using Min-Hash.

Privacy-Preserving Outlier Detection in Healthcare Services (IoT환경에서 프라이버시를 보장하는 의료데이터 이상치 탐색 기법)

  • Lee, Bo Young;Choi, Wonsuk;Lee, Dong Hoon
    • Journal of the Korea Institute of Information Security & Cryptology
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    • v.25 no.5
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    • pp.1187-1199
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    • 2015
  • Recently, as high-quality sensors are being developed, it is available to conveniently measure any kind of data. Healthcare services are being combined with Internet of things (IoTs). And applications that use user's data which are remotely measured, such as heart rate, blood oxygen level, temperature are emerging. The typical example is applications that find ideal spouse by using a user's genetic information, or indicate the presence or absence of a disease. Such information is closely related to the user's privacy, so biometric information must be protected. That is, service provider must provide the service while preserving user's privacy. In this paper, we propose a scheme which enables privacy-preserving outlier detection in Healthcare Service.

Genetic Symmetric Key Generation for IDEA

  • Malhotra, Nandini;Nagpal, Geeta
    • Journal of Information Processing Systems
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    • v.11 no.2
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    • pp.239-247
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    • 2015
  • Cryptography aims at transmitting secure data over an unsecure network in coded version so that only the intended recipient can analyze it. Communication through messages, emails, or various other modes requires high security so as to maintain the confidentiality of the content. This paper deals with IDEA's shortcoming of generating weak keys. If these keys are used for encryption and decryption may result in the easy prediction of ciphertext corresponding to the plaintext. For applying genetic approach, which is well-known optimization technique, to the weak keys, we obtained a definite solution to convert the weaker keys to stronger ones. The chances of generating a weak key in IDEA are very rare, but if it is produced, it could lead to a huge risk of attacks being made on the key, as well as on the information. Hence, measures have been taken to safeguard the key and to ensure the privacy of information.

Protection of Human Genetic Information and Citizens Participation (인간 유전정보 보호와 시민참여)

  • Lee Young-Hee;Kim Myoung-Jin;Kim Byoung-Soo
    • Journal of Science and Technology Studies
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    • v.3 no.1 s.5
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    • pp.41-73
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    • 2003
  • Personal genetic information is information about a person's genetic characteristics, which may reveal important information about private matters such as susceptibility to disease. Progress in genetics makes it much easier to obtain personal genetic information, and this leads to concerns about confidentiality and security of genetic information, and about possible genetic discrimination. This paper examines social issues related to human genetic information in terms of individual identification, diagnosis of diseases, and non-medical genetic test, and then tries to provide desirable citizens participation methods that can be used when making public policies related to genetic information protection.

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The Medical Information Protection and major Issues (의료정보 유출의 문제점과 의료정보보호)

  • Jeun, Young-Ju
    • Journal of the Korea Society of Computer and Information
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    • v.17 no.12
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    • pp.251-258
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    • 2012
  • The protection of medical information by major Issues on medical information to protect the individuals' privacy on medical information. Especially, Issues of medical service information, medical record, insurance, employment, Genetic technology including genetic test and screening, gene therapy and genetic enhancement is developing rapidly. Defensibility of medical information documentation is tested in the courts. medical information can be illicitly accessed from anywhere and transmitted across the quickly and with risk of detection. Once data is distributed on the internet, it may become available to anyone who wishes to purchase it, and it cannot be expunge. Patient privacy protection of medical information is controlled mostly by patient consent laws that define how and when a patient must consent before a physician may disclose the patient's medical information to anyone else. enterprise that offers consumers commodities or services is checking problem about customer information of management system is checking problem about customer information of management system essentially. Therefore, in this paper will find a way out to Protection of medical information by major Issues on medical information.

The Need for Homomorphic Encryption to Protection Privacy (프라이버시 보호를 위한 동형암호의 필요성)

  • Seo, Jin-Beom;Cho, Young-Bok
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2021.10a
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    • pp.47-49
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    • 2021
  • According to the revision of the Data 3 Act in 2020, personal information of medical data can be processed anonymously for statistical purposes, research, and public interest record keeping. However, unidentified data can be re-identified using genetic information, credit information, etc., and personal health information can be abused as sensitive information. In this paper, we derive the need for homomorphic encryption to protect the privacy of personal information separated by sensitive information.

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Optimization of Data Placement using Principal Component Analysis based Pareto-optimal method for Multi-Cloud Storage Environment

  • Latha, V.L. Padma;Reddy, N. Sudhakar;Babu, A. Suresh
    • International Journal of Computer Science & Network Security
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    • v.21 no.12
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    • pp.248-256
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    • 2021
  • Now that we're in the big data era, data has taken on a new significance as the storage capacity has exploded from trillion bytes to petabytes at breakneck pace. As the use of cloud computing expands and becomes more commonly accepted, several businesses and institutions are opting to store their requests and data there. Cloud storage's concept of a nearly infinite storage resource pool makes data storage and access scalable and readily available. The majority of them, on the other hand, favour a single cloud because of the simplicity and inexpensive storage costs it offers in the near run. Cloud-based data storage, on the other hand, has concerns such as vendor lock-in, privacy leakage and unavailability. With geographically dispersed cloud storage providers, multicloud storage can alleviate these dangers. One of the key challenges in this storage system is to arrange user data in a cost-effective and high-availability manner. A multicloud storage architecture is given in this study. Next, a multi-objective optimization problem is defined to minimise total costs and maximise data availability at the same time, which can be solved using a technique based on the non-dominated sorting genetic algorithm II (NSGA-II) and obtain a set of non-dominated solutions known as the Pareto-optimal set.. When consumers can't pick from the Pareto-optimal set directly, a method based on Principal Component Analysis (PCA) is presented to find the best answer. To sum it all up, thorough tests based on a variety of real-world cloud storage scenarios have proven that the proposed method performs as expected.