Gathering Of Personal Information Research Articles

Privacy Harm and Non-Compliance from a Legal Perspective

In today's data-sharing paradigm, personal data has become a valuable resource that intensifies the risk of unauthorized access and data breach. Increased data mining techniques used to analyze big data have posed significant risks to data security and privacy. Consequently, data breaches are a significant threat to individual privacy. Privacy is a multifaceted concept covering many areas, including the right to access, erasure, and rectify personal data. This paper explores the legal aspects of privacy harm and how they transform into legal action. Privacy harm is the negative impact to an individual as a result of the unauthorized release, gathering, distillation, or expropriation of personal information. Privacy Enhancing Technologies (PETs) emerged as a solution to address data privacy issues and minimize the risk of privacy harm. It is essential to implement privacy enhancement mechanisms to protect Personally Identifiable Information (PII) from unlawful use or access. FIPPs (Fair Information Practice Principles), based on the 1973 Code of Fair Information Practice (CFIP), and the Organization for Economic Cooperation and Development (OECD), are a collection of widely accepted, influential US codes that agencies use when evaluating information systems, processes, programs, and activities affecting individual privacy. Regulatory compliance places a responsibility on organizations to follow best practices to ensure the protection of individual data privacy rights. This paper will focus on FIPPs, relevance to US state privacy laws, their influence on OECD, and reference to the EU General Data Processing Regulation. (GDPR).

How Did You Get My Information? The Influence of Personal Information Gathering Methods on Social Media Advertising Effectiveness

The purpose of this study is to investigate the relationship between various consumer data collection techniques and privacy issues, and how these issues impact the effectiveness of social media advertising. In a study conducted online, it was discovered that when people are exposed to advertisements based on data collected from sources other than the website the advertisement is displayed on, their privacy concerns are at their peak. Due to worries over privacy, social media users are less likely to share advertisements on these platforms. Advertisers are advised to forbid the collection of consumer information via improper means in order to achieve satisfactory advertising effectiveness. The development of a privacy-protecting environment is also encouraged through societal actions.

Problems with surveillance capitalism and possible alternatives for IT infrastructure

ABSTRACT Over the past two decades, the business model of surveillance capitalism has emerged in the IT industry. This model has turned out to be highly profitable, but, if left unchecked, will very likely undermine the foundations of liberal democracies and quality of life on this planet. It involves customized advertising and behavior manipulation, powered by intensive gathering and cross-correlation of personal information. There are significant indirect costs of this model, including loss of privacy, supporting surveillance by both the state and corporations, undermining the democratic process, other kinds of automated attempts of behavior manipulation, and excessive consumerism with its attendant environmental costs. Turning to what could be done, we propose a co-development of regulation and technology, as well as the key roles that can be played by citizens and civil society organizations. The regulatory measures are intended to safeguard privacy, require true informed consent, and to foster interoperability (even among rival firms, nonprofit organizations, and others). We also identify key enabling technologies, including open source, APIs to support interoperability and portability, encryption, and peer-to-peer systems. Finally, we discuss the crucial role of ownership structures for these IT services and argue for an ecosystem approach as a counter narrative to surveillance capitalism.

Covid-19 and Employee Surveillance

While working from home is not a new concept, the advent of the Covid-19 pandemic has, for many in the workforce, rendered it the ‘new normal’, concomitant with enhanced use of workplace surveillance technologies to monitor and track staff working from home. Even prior to the global pandemic, organisations were increasingly using a variety of electronic surveillance methods to monitor their employees and the places where they work, whether it be in an office building or remotely. This technology traverses various facets of the work environment, including email communications, web browsing, the use of active badges for locating and tracking employees, and the gathering of personal information by employers. The application of these technologies, nevertheless, raises privacy concerns, which are exacerbated when work is undertaken in employees’ own homes, a phenomenon that has become more prevalent due to Covid-19. This article addresses the issue of electronic workplace monitoring, its implications for employees’ privacy and the role of collective bargaining in addressing this emergent practice, which has also been given new impetus during the pandemic.

Helping medical educators worldwide to pivot curricula online: pivotmeded.com.

The coronavirus disease 2019 (COVID-19) pandemic has resulted in the implementation of restrictions on group gatherings and educational events in many countries, creating imperatives for medical educators to move curricula online at short notice. Within medical schools and health sciences programmes, this urgency was compounded by competing priorities of health care delivery as many medical educators are also clinicians. To support medical educators, faculty development leaders in Canadian medical schools (FacDevCanada) collaborated to curate medical education resources in three categories: guidance on pivoting to online curriculum (classroom and clinical) delivery; discipline-specific learning resources, and general resources (including basic science, Indigenous health, patient safety and leadership development resources). The FacDevCanada developed PIVOTMeded (Partners in Virtual and Online Teaching in Medical Education), found at pivotmeded.com. Members of FacDevCanada crowdsourced resources in the three categories described above. Resource nominations were reviewed according to the following criteria: open accessibility; lack of evident bias; lack of (or minimal) personal information gathering, and relevance to the likely needs of learners and medical educators. A Google Site platform (Google LLC, Mountain View, CA, USA) was utilised in view of: (a) the platform's relative programming ease; (b) user navigation ease; (c) the platform's facilitation of responsive and dynamic displays compatible with computers, tablets and mobile devices, and (d) the curators' familiarity with the platform. Initially, one person reviewed nominations from contributors and sought materials for inclusion. Two additional medical educators with adeptness in curating resources and configuring the website became co-editors. Two administrative staff supported resource posting and website maintenance. Each resource's post includes a link and a customised annotation. PIVOTMeded launched on 17 March 2020. By 28 April (at the time of writing), the site had 2007 unique users. This indicates a high rate of utilisation; in comparison, a well-established open-access resource for family medicine educators, ‘learnfm.ca,’1 had 1265 unique users in the same 6 weeks. To date, we have curated 84 open-access resources, which support medical educators to pivot curricula online. Content comes from a variety of authors and multiple countries. Users come from 74 countries; the largest cohorts are from Canada (48%) and the USA (24%), followed by Portugal, the United Kingdom and Mexico (3% each). Half of website users visited directly (eg, by typing ‘pivotmeded.com’ into a browser), which suggests awareness of this website by name. One-third of users came through social media links and posts by individuals and organisations including the Association for Medical Education in Europe, the Royal College of Physicians and Surgeons of Canada, the College of Family Physicians of Canada, the Harvard Macy Institute, and faculty development units (all utilisation data from Google Analytics [Google LLC, Mountain View, CA, USA]). Key lessons learned refer to: (a) the value of an easily memorable name and URL (uniform resource locator) for this kind of project; (b) the importance of curating site content selectively rather than providing links to a large number of resources (as evidenced by spontaneous feedback and tweets about our project); (c) the need to have multiple people collaborate on this type of project (to ensure high-quality curation within a tight time frame), and (d) the value of tweets, posts and emails from established individuals and organisations in building awareness. Beyond COVID-19, pivotmeded.com will continue to curate open-access materials supporting online medical education.

Federated learning framework for mobile edge computing networks

The continuous growth of smart devices needing processing has led to moving storage and computation from cloud to the network edges, giving rise to the edge computing paradigm. Owing to the limited capacity of edge computing nodes, the presence of popular applications in the edge nodes results in significant improvements in users’ satisfaction and service accomplishment. However, the high variability in the content requests makes prediction demand not trivial and, typically, the majority of the classical prediction approaches require the gathering of personal users' information at a central unit, giving rise to many users' privacy issues. In this context, federated learning gained attention as a solution to perform learning procedures from data disseminated across multiple users, keeping the sensitive data protected. This study applies federated learning to the demand prediction problem, to accurately forecast the more popular application types in the network. The proposed framework reaches high accuracy levels on the predicted applications demand, aggregating in a global and weighted model the feedback received by users, after their local training. The validity of the proposed approach is verified by performing a virtual machine replica copies and comparison with the alternative forecasting approach based on chaos theory and deep learning.

Microservice chatbot architecture for chronic patient support.

Chatbots are able to provide support to patients suffering from very different conditions. Patients with chronic diseases or comorbidities could benefit the most from chatbots which can keep track of their condition, provide specific information, encourage adherence to medication, etc. To perform these functions, chatbots need a suitable underlying software architecture. In this paper, we introduce a chatbot architecture for chronic patient support grounded on three pillars: scalability by means of microservices, standard data sharing models through HL7 FHIR and standard conversation modeling using AIML. We also propose an innovative automation mechanism to convert FHIR resources into AIML files, thus facilitating the interaction and data gathering of medical and personal information that ends up in patient health records. To align the way people interact with each other using messaging platforms with the chatbot architecture, we propose these very same channels for the chatbot-patient interaction, paying special attention to security and privacy issues. Finally, we present a monitored-data study performed in different chronic diseases, and we present a prototype implementation tailored for one specific chronic disease, psoriasis, showing how this new architecture allows the change, the addition or the improvement of different parts of the chatbot in a dynamic and flexible way, providing a substantial improvement in the development of chatbots used as virtual assistants for chronic patients.

A homomorphic encryption-based system for securely managing personal health metrics data

Hardware and software solutions for the collection of personal health information continue to evolve. The reliable gathering of personal health information, previously usually possible only in dedicated medical settings, has recently become possible through wearable specialized medical devices. Among other drawbacks, these devices usually do not store the data locally and offer, at best, limited basic data processing features and few advanced processing capabilities for the collected personal health data. In this paper, we describe an integrated personal health information system that allows secure storage and processing of medical data in the cloud by using a comprehensive homomorphic encryption model to preserve data privacy. The system collects the user data through a client application module, typically installed on the user's smartphone or smartwatch, and securely transports the data to the cloud backend powered by IBM Bluemix. The data are stored by the IBM Cloudant infrastructure, while the homomorphic processing of the encrypted data is performed using the Apache Spark service, which is also made available by the IBM Bluemix platform. The event-based handlers are triggered by the IBM OpenWhisk programming service. The initial prototype has been tested using a real-world use case, which is described.

個人による情報収集からコミュニティベースの論点設定へ : ウェブ技術の進化による価値創造プロセスの変化( 情報の収集と発信)

個人による情報収集からコミュニティベースの論点設定へ : ウェブ技術の進化による価値創造プロセスの変化( 情報の収集と発信)

Personalized Information Gathering in a Multiple Personal Device Environment

We propose a personalized information gathering system PerIGS that exploits implicit user feedback in a multiple personal device environment. PerIGS extracts imposing words that induce user's choice from recommended news articles, and constructs user preference profile based on observed user behaviors. A user profile is shared by multiple personal devices, and PerIGS gathers, filters, and recommends news articles according to this shared profile. We organize the user profile in a hierarchical category structure to deal with the uncertainty of user interests. This structure also enables the system to track and recognize the changes of user interests for each domain more effectively. The results of a series of experiments measuring user satisfaction for recommended news articles indicated that PerIGS can effectively utilize user profiles for news filtering and recommendation.

The Quest for Information Privacy in Africa: A Review Essay

The Quest for Information Privacy in Africa: A Review Essay

Anthropogenic noise alters dwarf mongoose responses to heterospecific alarm calls

Anthropogenic noise is an evolutionarily novel and widespread pollutant in both terrestrial and aquatic habitats. Despite increasing evidence that the additional noise generated by human activities can affect vocal communication, the majority of research has focused on the use of conspecific acoustic information, especially sexual signals. Many animals are known to eavesdrop on the alarm calls produced by other species, enhancing their likelihood of avoiding predation, but how this use of heterospecific information is affected by anthropogenic noise has received little empirical attention. Here, we use two field-based playback experiments on a habituated wild population of dwarf mongooses (Helogale parvula) to determine how anthropogenic noise influences the response of foragers to heterospecific alarm calls. We begin by demonstrating that dwarf mongooses respond appropriately to the alarm calls of sympatric chacma baboons (Papio ursinus) and tree squirrels (Paraxerus cepapi); fleeing only to the latter. We then show that mongoose foragers are less likely to exhibit this flee response to tree squirrel alarm calls during road-noise playback compared to ambient-sound playback. One explanation for the change in response is that noise-induced distraction or stress result in maladaptive behaviour. However, further analysis revealed that road-noise playback results in increased vigilance and that mongooses showing the greatest vigilance increase are those that do not subsequently exhibit a flee response to the alarm call. These individuals may therefore be acting appropriately: if the greater gathering of personal information indicates the absence of an actual predator despite an alarm call, the need to undertake costly fleeing behaviour can be avoided. Either way, our study indicates the potential for anthropogenic noise to interfere with the use of acoustic information from other species, and suggests the importance of considering how heterospecific networks are affected by this global pollutant.

A Personalized Ontology Model For Web Mining Using Instance Matching

In rapid growth of internet, the amount of web information gathering becomes a challenging point for all users. Many existing retrieval systems have been developed to attempt to satisfy this problem. But still there is no complete solution to the problem. Ontology describes and formalizes standardized representation of knowledge as a set of concepts and the relationship between those concepts. In personalized web information gathering ontology is also used to represent the user profiles. For representing user profiles many existing models have been provided knowledge from either global or local knowledge base. The user background knowledge can be better discovered if we integrate global and local analysis. The proposed system emphasizes the specific semantic relation in one computational model. Ontology contains lots of instances. Automatically instance matching has become the fundamental issue. Instance matching approach is used to present based on discriminative property value. Ontology model in domain specific system with instance

The Angel on Your Shoulder: Prompting Employees to Do the Right Thing Through the Use of Wearables

The wearable revolution is upon us. Bulky chest straps and large wristbands are going the way of flip cellphones and floppy disks. In the near future, for example, it may be commonplace for athletes to wear Biostamps or smart T-shirts with embedded sensors during practices, games, and even sleep. And while athletic competitors may have been one of the first movers in the area, health care, the military, and the industrial sector have all begun to use wearables to harness vast treasure troves of information destined to provide highly individualized feedback. The possibilities are almost endless when such personal information is combined with big data analytics in the name of improving large-scale efficiency.Interestingly, employers were one of the first movers in the wearable revolution. Yet, other than basic tracking of people and goods, there is still a tremendous potential for expansion. What if wearables could be harnessed to assist employees in avoiding conflict of interests? What if wearables could assist employees in identifying ethical dilemmas and could then prompt them to consider alternative courses of action? What if the wearable evolution became an ethical revolution?But the drawbacks of using wearables in such a manner must also be critically analyzed. This Article takes this step by exploring the use of wearables as personal information gathering devices that feed into larger data sets. It then considers some of the legal and policy implications of the use and aggregation of data in such a manner and ultimately makes suggestions for bottom-up baseline regulation. Ultimately, we argue for the desirability of leveraging this emerging technology, subject to privacy and security safeguards, to help drive an ethical revolution in business cultures.

The Protection of Personal Information and the Principle of Proportion in Information Societies

With the realization that the police's personal information gathering activities can violate the authority to decide one's information guaranteed by the Constitution, many people are interested in the legal terms of the police's information gathering and handling. The police's personal information gathering activities imply both the purpose of public welfare and order and the risk of violation of basic rights of citizens, their effective balance is critical. In this respect, this study reviews the principle of proportion as a principle of control of personal information gathering and handling (police intelligence activities) by state to discuss its implications on legislation.

How Does Taste In Educational Settings Influence Parent Decision Making Regarding Enrolment?

How Does Taste In Educational Settings Influence Parent Decision Making Regarding Enrolment?

Personalized multi-modality image management and search for mobile devices

Mobile devices are quickly becoming a primary medium for personal information gathering, management, and sharing. Managing personal image data on mobile platforms is a challenging problem due to la...

E-Commerce and Privacy: Exploring What We Know and Opportunities for Future Discovery

ABSTRACT Electronic commerce (e-commerce) has a built-in trade-off between the necessity of providing at least some personal information to consummate an online transaction and the risk of negative consequences from providing such information. This requirement and the increased sophistication of companies' personal information gathering have made e-commerce privacy a critical issue and have spawned a broad research literature that is reviewed in this paper. Key research issues and findings are organized, using a framework defined by four key stakeholder groups—companies, customers, privacy solution providers (PSPs), and governments—as well as the interactions among them. The review indicates that the published research on e-commerce privacy peaked in the early 2000s; thus, it has not addressed many of the technological advances and other relevant developments of the past decade. Potential research opportunities for researchers in Management Information Systems (MIS) and Accounting Information Systems (AIS) include: company privacy strategies, operations, disclosures, and compliance practices; customer privacy concerns arising from company practices such as Internet activity tracking, physical location tracking, personal information gathering by social networks, and information exchanges in cloud computing environments; privacy-enhancing technologies, controls, and assurance practices developed by PSPs; and privacy regulations relating to various industries, countries, and cultures. More use of experimental and archival research is encouraged.

Detailed analysis of consumption of the transport device by the mobile device

This paper deals with the gathering of GPS data and other personal information that iares used to calculate the consumption of motor vehicles. To create a basic test application for the measurement consumption (Microsoft Visual Studio, 2008), C # programming language was used. The application is designed for devices based on Windows Mobile. For testing, a few PDA devices with integrated GPS module were used. The application calculated the consumption of refuel liters (yet entered by the user) with regard to mileage, which was determined from the read coordinates of a GPS module. This information is then stored in a SQL database for further analysis. To minimize errors will aid in using the algorithms to calculate the distance in 3D space. The application reached accuracy using a suitably chosen sampling interval. The result is a relatively simple test application for the Windows Mobile platform. Key words: GPS NMEA, distance calculation, windows mobile, measurement consumption.

Online Privacy Concerns Of Indian Consumers

This paper describes an empirical study that investigates the factors that influence consumers’ online privacy concerns and their outcomes in the rapidly growing Indian online market. Indian consumers’ online privacy concerns are found to be positively impacted by their perceived vulnerability to unauthorized gathering and use of personal information, and negatively impacted by their perceived ability to control the manner in which their personal information is collected and used online. The consumers’ perceived vulnerability is negatively affected by their level of Internet literacy and their perceived ability to control the collection and use of information. In turn, the perceived ability to control information collection and use is positively influenced by both the Internet literacy level and the social awareness of the consumer. The privacy concerns of Indian consumers are found to negatively impact both their willingness to provide personal information to Websites, and their willingness to engage in e-commerce transactions. The implications of the findings for Websites targeting the Indian audience are discussed.