Privacy-Preserved and Best-effort Provisions of Cyber-I Information to Personalized Services

Abstract—User information is needed for personalized services. However, personalized services are often confused either by information inconsistency and incorrectness or the cold start issue while they gather user information. Even some services, such as social network services, provide user information for personalized services to overcome these problems, they are also facing difficulty of the limited diversity of user information. Additionally, they are only capable of providing existing information. While a Cyber-I (short for Cyber Individual) collects any information of a person in its way to gradually approximate to its user. Certainly, a user information needed by personalized services is also included in a corresponding Cyber-I. Therefore, providing Cyber-I information to personalized services could be more prospecting. In order to provide Cyber-I information to personalized services, there are two main problems should be solved. One is the privacy protection problem. Methods should be designed to provide privacy preservation for user. Another one is the best-effort issue which is about how to make full use of existing Cyber-I information to satisfy personalized services as much as possible. Thus, the goal of this paper is providing Cyber-I information to personalized services by best-efforts provisions, simultaneously provide privacy preservation for Cyber-I. To reach that goal, a Cyber-I Information Provision System (CIPS) is proposed. Keywords—Cyber-I; Real-I; personalized service; privacy preservation; information provisio

Research and Development of a Cyber-I Open Service Platform

研究成果の概要 (和文) : Cyber-Iは、Real-Iのデジタル対応であり、個人データの収集と分析を行い、人の行動や感情に近づけます。本研究では、複数のデバイスから多くの個人データを収集して処理を行い、Cyber-Iの作成と管理を行うようなオープンサービスプラットフォームを開発しました。異なるデバイスやデータを柔軟でスケーラブルな管理をするために、スマートフォンをゲートウェイとして使用するクラウドやフォグベースのデータベースシステムを実装しています。また、Cyber-Iの成長をコントロールするような基本的技術やメカニズムを提案しています。さらにCyber-I関連における個人情報の保護と利用についても検討しています。研究成果の概要 (英文) : Cyber-I, short for Cyber Individual, is a digital counterpart of Real-Individual (Real-I), and is expected to continuously approximate a real person’s behavior and even mind with collections and analyses of increasing personal data. In this research, a Cyber-I open service platform has been researched and developed to collect and process rich personal big data from various sources and multiple devices for Cyber-I creation and administration as well as its modeling and life control. A cloud-fog based database system using smartphones as gateways has been implemented for flexible and scalable managements of heterogeneous devices and data. Basic strategy and mechanism have been proposed for scheduling and controlling Cyber-I growth. Cyber-I related data privacy protection and personal information usage are also studied. A series of researches on personality and affective computing has been carried out to model personal characteristics

Compliance Elliance Journal: Compliance between Adaption and Advance

Compliance organization and compliance function must constantly evolve and be adaptable, both through further development within the company and changes in the political and legal situations in which companies operate. In this issue, we kick off with a piece of thought in which Michele DeStefano (Content Curator) engages with experts from compliance practice, including Markus Endres (Advisory Board CEJ) on the question: What role can and should compliance play in digital transformation in the enterprise? From a legal perspective, it is clear that determining the 'role' of compliance is exceedingly relevant, if only because of liability. Furthermore, our authors in this issue deal with the 'Monaco Memo' and its significance for antitrust investigation in the USA and with the continuing relevant topic of sanctions compliance. In addition, our authors from Austria and Liechtenstein describe the implementation of an effective compliance management system in the company and the Compliance Officer’s duty to monitor

Reining in the Big Promise of Big Data: Transparency, Inequality, and New Regulatory Frontiers

The growing differentiation of services based on Big Data harbors the potential for both greater societal inequality and for greater equality. Anti-discrimination law and transparency alone, however, cannot do the job of curbing Big Data’s negative externalities while fostering its positive effects. To rein in Big Data’s potential, we adapt regulatory strategies from behavioral economics, contracts and criminal law theory. Four instruments stand out: First, active choice may be mandated between data collecting-services (paid by data) and data-free services (paid by money). Our suggestion provides concrete estimates for the price range of a data-free option, sheds new light on the monetization of data-collecting services, and proposes an “inverse predatory pricing” instrument to limit excessive pricing of the data-free option. Second, we propose using the doctrine of unconscionability to prevent contracts that unreasonably favor data-collecting companies. Third, we suggest democratizing data collection by regular user surveys and data compliance officers partially elected by users. Finally, we trace back new Big Data personalization techniques to the old Hartian precept of treating like cases alike and different cases – differently. If it is true that a speeding ticket over $50 is less of a disutility for a millionaire than for a welfare recipient, the income and wealth-responsive fines powered by Big Data that we suggest offer a glimpse into the future of the mitigation of economic and legal inequality by personalized law. Throughout these different strategies, we show how salience of data collection can be coupled with attempts to prevent discrimination and exploitation of users. Finally, we discuss all four proposals in the context of different test cases: social media, student education software and credit and cell phone markets. Many more examples could and should be discussed. In the face of increasing unease about the asymmetry of power between Big Data collectors and dispersed users, about differential legal treatment, and about the unprecedented dimensions of economic inequality, this paper proposes a new regulatory framework and research agenda to put the powerful engine of Big Data to the benefit of both the individual and societies adhering to basic notions of equality and non-discrimination

EU policies in data governance : the new challenge on the field of public administration.

Διπλωματική εργασία--Πανεπιστήμιο Μακεδονίας, Θεσσαλονίκη, 2019It is an analytic study in the new sector of policy and decision making of European Union. In the following project i will try to research and categorize the sectors( security, science, economy, environment, geopolicy, external policies) in which data governace effects the day to day work and life of european citizens, how it defines and involve with the constitutionals rules and laws of European Union's internal polices but also its external policies( USA , China, Russia). Furthermore, this study will show the progressively steps of EU in comparison with other developed countries and international organizations and also will examinate the policies of data governance, in private and public sector, across the globe

Beyond Protecting Genetic Privacy: Understanding Genetic Discrimination Through its Disparate Impact on Racial Minorities

At the very end of the last century, scientists produced the first draft of the whole human genetic sequence. But that was just the first step; the hard work of the first few decades of this century will be to learn more about how to apply genetic information to improve health. As the pace of technological development accelerates and we learn more about what genetic variations mean about individual human characteristics and health risks, so too does the risk and consequences of the misuse of such information become more significant. The principal answer to this challenge has been to safeguard privacy by constructing legal and technical barriers that conceal and anonymize genetic information. While it may be a worthwhile objective, ultimately privacy protections will likely fail in practice. If this is so, how can we prevent genetic information from being used to categorize, stigmatize, and subordinate? This Note approaches this problem by analyzing the African American experience with genetic discrimination in the United States. African Americans have confronted the adverse consequences of genetic research in ways that can serve as a foundation to understand future threats posed to racial minorities and everyone in society, as genetic testing increases in prevalence and the privacy of genetic information is unable to be protected. Studying the real history of genetic discrimination, rather than merely speculating about what may happen, can point toward policy solutions that go beyond ―genetic privacy.‖ As genetic information becomes more plentiful and valuable, policies to prevent the misuse of that information will benefit everyone, regardless of race or ethnicity

Small Pool for Big Data: Researching for Sustainable Data Focused on Open Government Data (OGD) Movement

When Sir Isaac Newton said his famous statement standing on the shoulders of giants, it was a modest phrase and explained the necessity of sharing knowledge or information to make the next intellectual progress. The data industry is now the fastest developing area, but many ambiguities are a subject in law. The protection of data is a fascinating and still unsolved challenge for intellectual property law. Data is essential in the matter of new industry and our lifestyle at individual, corporate, and institutional levels. And the legal protection needs to work to offer vivid transactions of data for creative interactions. However, many enterprises consider data an asset for business profit as the data industry grows vast and fast. Data raises diverse policy debates that arise in the better-known intellectual property areas, for instance, copyrights, unfair competition, and trade secret. The vague aspects of data implicate a number of intellectual property approaches. It also extends to the economic problem \u27tragedy of anti-commons\u27 that fragmented ownership is disrupting sound usage. In this regard, Open Governmental Data (OGD) is one way to resolve inefficiency in the data industry. The government collects massive personal data and reproduces datasets in the process of administration. Many governments give back the public data for private sectors anticipating the data works for new enterprise seed money. This work looks at three considerations about the legal aspects of data. At first, we will see the necessity of big data in current and reasons for the government to pay attention to open data to the public. The data industry market\u27s inefficiency discourages cumulative innovation in our society and approaches the benefits of sharing data in the private economy or OGD movement. Second, the paper conducts principles of OGD and takes a functional approach in analyzing the related IP laws in database protection and public accessibility. Interestingly various governments are opening data that compares various OGD models from different countries led by other stakeholders, including government, large companies, small to medium enterprises ( SMEs ), and how they work as a member of OGD. Finally, it critiques the current OGD movement and suggests that corporate OGD strategies granting autonomous would help resolve the anti-commons of IP in the big data industry

COVID-19 & privacy: Enhancing of indoor localization architectures towards effective social distancing

Abstract The way people access services in indoor environments has dramatically changed in the last year. The countermeasures to the COVID-19 pandemic imposed a disruptive requirement, namely preserving social distance among people in indoor environments. We explore in this work the possibility of adopting the indoor localization technologies to measure the distance among users in indoor environments. We discuss how information about people's contacts collected can be exploited during three stages: before, during, and after people access a service. We present a reference architecture for an Indoor Localization System (ILS), and we illustrate three representative use-cases. We derive some architectural requirements, and we discuss some issues that concretely cope with the real installation of an ILS in real-world settings. In particular, we explore the privacy and trust reputation of an ILS, the discovery phase, and the deployment of the ILS in real-world settings. We finally present an evaluation framework for assessing the performance of the architecture proposed

Revolutionizing Healthcare Organizations with Operational Excellence and Healthcare 4.0: A Systematic Review of the State-of-the-Art Literature

Purpose- This study examines current research on the relationship between Operational Excellence and Healthcare 4.0 for healthcare organizations. Design/Methodology/Approach- We have performed a systematic literature review of 102 documents published between 2011 to 2022 from the Scopus database to identify the research trends on Operational Excellence and Healthcare 4.0. Through a descriptive bibliometric analysis, we have highlighted the year-wise trend in publication, top authors, prominent sources of publications, the country-wise spread of research activities, and subject area analysis. Further, through content analysis, we have identified four clusters and proposed directions for future research of each identified cluster. Findings- Results reflect overall growth in this area, with a few parts of the world being underrepresented in research related to Operational Excellence and Healthcare 4.0. The content analysis focused on describing challenges pertaining to healthcare industries and the role of Operational Excellence tools and Healthcare 4.0 technologies in dealing with various healthcare delivery aspects. We concluded our analysis by proposing a theoretical framework and providing theoretical and managerial implications of the study. Originality- The article is one of the first to analyze the existing literature on the healthcare sector at the interface of Operational Excellence and Healthcare 4.0 technologies. The conceptual framework and cluster-wise future research prepositions are some of the unique offerings of the study