User Consent Research Articles

Wearable IoTs and Geo-Fencing Based Framework for COVID-19 Remote Patient Health Monitoring and Quarantine Management to Control the Pandemic

The epidemic disease of Severe Acute Respiratory Syndrome (SARS) called COVID-19 has become a more frequently active disease. Managing and monitoring COVID-19 patients is still a challenging issue for advanced technologies. The first and foremost critical issue in COVID-19 is to diagnose it timely and cut off the chain of transmission by isolating the susceptible and patients. COVID-19 spreads through close interaction and contact with an infected person. It has affected the entire world, and every country is facing the challenges of having adequate medical facilities along with the availability of medical staff in rural and urban areas that have a high number of patients due to the pandemic. Due to the invasive method of treatment, SARS-COVID is spreading swiftly. In this paper, we propose an intelligent health monitoring framework using wearable Internet of Things (IoT) and Geo-fencing for COVID-19 susceptible and patient monitoring, and isolation and quarantine management to control the pandemic. The proposed system consists of four layers, and each layer has different functionality: a wearable sensors layer, IoT gateway layer, cloud server layer, and client application layer for visualization and analysis. The wearable sensors layer consists of wearable biomedical and GPS sensors for physiological parameters, and GPS and Wi-Fi Received Signal Strength Indicator acquisition for health monitoring and user Geo-fencing. The IoT gateway layer provides a Bluetooth and Wi-Fi based wireless body area network and IoT environment for data transmission anytime and anywhere. Cloud servers use Raspberry Pi and ThingSpeak cloud for data analysis and web-based application layers for remote monitoring based on user consent. The susceptible and patient conditions, real-time sensor’s data, and Geo-fencing enables minimizing the spread through close interaction. The results show the effectiveness of the proposed framework.

State of the Art in Adoption of Contact Tracing Apps and Recommendations Regarding Privacy Protection and Public Health: Systematic Review.

BackgroundDuring the COVID-19 pandemic, contact tracing apps have received a lot of public attention. The ongoing debate highlights the challenges of the adoption of data-driven innovation. We reflect on how to ensure an appropriate level of protection of individual data and how to maximize public health benefits that can be derived from the collected data.ObjectiveThe aim of the study was to analyze available COVID-19 contact tracing apps and verify to what extent public health interests and data privacy standards can be fulfilled simultaneously in the process of the adoption of digital health technologies.MethodsA systematic review of PubMed and MEDLINE databases, as well as grey literature, was performed to identify available contact tracing apps. Two checklists were developed to evaluate (1) the apps’ compliance with data privacy standards and (2) their fulfillment of public health interests. Based on both checklists, a scorecard with a selected set of minimum requirements was created with the goal of estimating whether the balance between the objective of data privacy and public health interests can be achieved in order to ensure the broad adoption of digital technologies.ResultsOverall, 21 contact tracing apps were reviewed. In total, 11 criteria were defined to assess the usefulness of each digital technology for public health interests. The most frequently installed features related to contact alerting and governmental accountability. The least frequently installed feature was the availability of a system of medical or organizational support. Only 1 app out of 21 (5%) provided a threshold for the population coverage needed for the digital solution to be effective. In total, 12 criteria were used to assess the compliance of contact tracing apps with data privacy regulations. Explicit user consent, voluntary use, and anonymization techniques were among the most frequently fulfilled criteria. The least often implemented criteria were provisions of information about personal data breaches and data gathered from children. The balance between standards of data protection and public health benefits was achieved best by the COVIDSafe app and worst by the Alipay Health Code app.ConclusionsContact tracing apps with high levels of compliance with standards of data privacy tend to fulfill public health interests to a limited extent. Simultaneously, digital technologies with a lower level of data privacy protection allow for the collection of more data. Overall, this review shows that a consistent number of apps appear to comply with standards of data privacy, while their usefulness from a public health perspective can still be maximized.

Direct‐to‐consumer genetic testing in China and its role in GWAS discovery and replication

BackgroundThe direct‐to‐consumer genetic testing (DTC‐GT) industry has exploded in recent years, initiated by market pioneers from the United States and quickly followed by companies from Europe and Asia. In addition to their primary objective of providing ancestry and health information to customers, DTC‐GT services have emerged as a valuable data resource for large‐scale population and genetics studies.MethodsWe assessed DTC‐GT market leaders in the U.S. and China, user participation in research, and academic reports based on this information. We also investigated DTC‐GT end‐user value by tracing key updates of companies provided via health risk reports and evaluating their predictive power. We then assessed the replicability of several genome‐wide association studies (GWAS) based on a Chinese DTC‐GT biobank.ResultsAs recent entrants to the market, Chinese DTC‐GT service providers have published less academic research than their Western counterparts; however, a larger proportion of Chinese users consent to participate in research projects. Dramatic increases in user volume and resultant report updates led to reclassification of some users’ polygenic risk levels, but within a reasonable scale and with increased predictive power. Replicability among GWAS using the Chinese DTC‐GT biobank varied by studied trait, population background, and sample size.ConclusionsWe speculate that the rapid growth in DTC‐GT services, particularly in non‐Caucasian populations, will yield an important and much‐needed resource for biobanking, large‐scale genetic studies, clinical trials, and post‐clinical applications.

Trust, but Verify: Informed Consent, AI Technologies, and Public Health Emergencies

To use technology or engage with research or medical treatment typically requires user consent: agreeing to terms of use with technology or services, or providing informed consent for research participation, for clinical trials and medical intervention, or as one legal basis for processing personal data. Introducing AI technologies, where explainability and trustworthiness are focus items for both government guidelines and responsible technologists, imposes additional challenges. Understanding enough of the technology to be able to make an informed decision, or consent, is essential but involves an acceptance of uncertain outcomes. Further, the contribution of AI-enabled technologies not least during the COVID-19 pandemic raises ethical concerns about the governance associated with their development and deployment. Using three typical scenarios—contact tracing, big data analytics and research during public emergencies—this paper explores a trust-based alternative to consent. Unlike existing consent-based mechanisms, this approach sees consent as a typical behavioural response to perceived contextual characteristics. Decisions to engage derive from the assumption that all relevant stakeholders including research participants will negotiate on an ongoing basis. Accepting dynamic negotiation between the main stakeholders as proposed here introduces a specifically socio–psychological perspective into the debate about human responses to artificial intelligence. This trust-based consent process leads to a set of recommendations for the ethical use of advanced technologies as well as for the ethical review of applied research projects.

PIN Inference Attack: A Threat to Mobile Security and Smartphone-Controlled Robots

The proliferation of smartphones equipped with various sensors created a large user base, which includes robots (smartphone controlled) as well. The high processor enabled smartphones are used as software robots to track hour-to-hour activities of users using on-board motion sensors. The magnetometer, accelerometer, and gyroscope are non-permission based motion sensors. The logs of these sensors create discriminative patterns to identify users’ movements. This leverages an adversary to cause privacy threats using these non-permission based sensors without user consent. Recent works also highlighted the privacy threats due to the motion sensors in smartphones. Therefore, in this paper, we present a potential misuse of technology where smartphones can be hacked by PIN Inference attack endangering the mobile security. Once the smartphone is compromised, it may lead to various repercussions. We discuss one such case where after PIN is inferred the adversary incorrectly uses our robot made for corridor detection. With this example, we show the severity of the PIN-Inference attack as nowadays many user activities are governed by robots. We perform experiments to collect motion sensors’ data and infer 4-digit PIN of a smartphone. Our strategy is to detect every key pressed one by one constituting a 4-digit PIN. Our inference results are promising and prove that an adversary can make use of sensors’ data to infiltrate user’s sensitive information from smartphones. Our proposed model infers 84% of the PINs correctly within 40 attempts when tested on 50 PINs. Given real Android devices with different users, we can identify the PIN of smartphones by training our machine learning based model. We also compare our approach with existing state-of-the-art approaches to show the efficacy of our attack model.

Integrating Blockchain With Artificial Intelligence for Privacy-Preserving Recommender Systems

Data privacy is one of the intriguing problems in e-commerce site. For personal or business purposes, users have to disclose their private data to these e-commerce sites. Often such businesses use these highly sensitive data for computing artificial intelligence-driven analyses like recommendation generation without user consent. In the case of recommendation generation, data need to be analyzed at the business platforms. An automated personalization, based on artificial intelligence, on a list of products with respect to user interest is generated by a recommender system. However, the secure utilization of user data is absent in such systems. This paper proposes Private-Rec , a privacy-preserving platform for a recommendation system through the integration of artificial intelligence and blockchain. In Private-Rec , blockchain gives the user a secure environment through the distributed attribute in which data can be used with the required permission. Under this platform, users receive incentives (i.e., point, discount) from the recommended company for sharing their data to be used for computing recommendations. The Private-Rec platform has been studied empirically.

``I don't care about cookies!" Platform Data Disclosure and Time-Inconsistent Users

Time-inconsistent internet users neglect future privacy costs and release too much data to be monetized by digital platforms. We study how regulations that require user consent for data processing affect platform profits, welfare and user surplus, depending on business models and the degree of time inconsistency. Consent mechanisms increase user surplus or welfare only if their design facilitates consent refusal. If platforms can make it difficult to opt out, it may be better for society as a whole if the former choose the disclosure level, even though it tends to be excessive from a user point of view. Voluntary caps on usage, as recently adopted by some platforms, can raise profits by making some users consent to more disclosure.

Computer firewalls: security and privacy protection for Mac—review

Internet has become the ultimate information resource. It allows both to reach information from the outside, as well as to share inside data. Yet, such power also involves potential weaknesses, in relation to security and privacy protection. Indeed, threats may come from malicious web sites, trying to steal user's data or install unwanted applications. Malware may include adware, Potentially Unwanted Applications (PUA) or Potentially Unwanted Programs (PUP), and even ransomware. Another menace may even come from otherwise bona fide applications installed by the user. Thus, such applications may send private data to external servers, without the user's consent and knowledge. Therefore, a proper firewall is required to protect the privacy of users. Indeed, they are built inside the operating systems, as basic security tools. Third party companies offer more comprehensive firewalls, including free and nonfree ones. This review analyzes the firewalls available for Mac (macOS) computers. As a practical example, applications in scientific research, in general, as well as bioinformatics, in particular, are described. Last but not least, Internet security and privacy protection is a work in progress, and as such, users should know about this critical fact, and take proper action, installing and updating appropriate firewalls.

(mis)Informed Consent in Australia

(mis)Informed Consent in Australia

Existence Results for a Computer Virus Spreading Model with Atangana-Baleanu Derivative

A computer virus is actually a kind of computer program that changes the operation of the computer and tries to hide itself in other files without the user's consent or knowledge. In this paper we deal with a computer virus spreading model benefiting from Atangana-Baleanu derivative in Caputo sense with non- local and non- singular kernels. The solution properties of our fractional model are established benefiting from Arzelo-Ascoli theorem.

Derecho a la información y protección de datos personales en el neoconstitucionalismo iberoamericano

El derecho a la información es uno de los derechos fundamentales consagrados enla Declaración Universal de los Derechos Humanos. En el mundo contemporáneo, en laera de la información, el acceso a ella se facilita como nunca en la historia, debido a quees posible transmitir datos de voz, texto y video en tiempo real. A pesar de la brechadigital que persiste en la región iberoamericana, es posible argumentar que esta se ha idocerrando de manera paulatina en los últimos años. La digitalización de la interacción social,la educación y los servicios públicos y privados se han convertido en una realidad tangible,con una enorme repercusión económica, social y política. Pero, también, los datos personales se encuentran, como nunca en la historia, expuestos a ser utilizados con fines ajenosal consentimiento del usuario. En el presente artículo buscaremos describir algunas de lasposibilidades y retos del derecho a la información y la protección a los datos personales.Igualmente, estudiaremos la manera en que ambos derechos deben ser protegidos porel constitucionalismo iberoamericano. El Estado mexicano no ha sido pionero en AméricaLatina en protección de datos personales, ni existen en su territorio garantías lo suficientemente efectivas para disuadir a los traficantes de datos que todos los días manipulany comercializan con ellos. No obstante, se han realizado los primeros intentos para transitar hacia un régimen más transparente, en el que el derecho de acceso a la informaciónpública sea un peldaño para fortalecer el tan debilitado Estado democrático de derecho.

Self-Monitoring App Preferences for Sun Protection: Discrete Choice Experiment Survey Analysis.

BackgroundThe availability and use of health apps continues to increase, revolutionizing the way mobile health interventions are delivered. Apps are increasingly used to prevent disease, improve well-being, and promote healthy behavior. On a similar rise is the incidence of skin cancers. Much of the underlying risk can be prevented through behavior change and adequate sun protection. Self-monitoring apps have the potential to facilitate prevention by measuring risk (eg, sun intensity) and encouraging protective behavior (eg, seeking shade).ObjectiveOur aim was to assess health care consumer preferences for sun protection with a self-monitoring app that tracks the duration and intensity of sun exposure and provides feedback on when and how to protect the skin.MethodsWe conducted an unlabeled discrete choice experiment with 8 unique choice tasks, in which participants chose among 2 app alternatives, consisting of 5 preidentified 2-level attributes (self-monitoring method, privacy control, data sharing with health care provides, reminder customizability, and costs) that were the result of a multistep and multistakeholder qualitative approach. Participant preferences, and thus, the relative importance of attributes and their levels were estimated using conditional logit modeling. Analyses consisted of 200 usable surveys, yielding 3196 observations.ResultsOur respondents strongly preferred automatic over manually operated self-monitoring (odds ratio [OR] 2.37, 95% CI 2.06-2.72) and no cost over a single payment of 3 Swiss francs (OR 1.72, 95% CI 1.49-1.99). They also preferred having over not having the option of sharing their data with a health care provider of their choice (OR 1.66, 95% CI 1.40-1.97), repeated over single user consents, whenever app data are shared with commercial thirds (OR 1.57, 95% CI 1.31-1.88), and customizable over noncustomizable reminders (OR 1.30, 95% CI 1.09-1.54). While most participants favored thorough privacy infrastructures, the attribute of privacy control was a relatively weak driver of app choice. The attribute of self-monitoring method significantly interacted with gender and perceived personal usefulness of health apps, suggesting that female gender and lower perceived usefulness are associated with relatively weaker preferences for automatic self-monitoring.ConclusionsBased on the preferences of our respondents, we found that the utility of a self-monitoring sun protection app can be increased if the app is simple and adjustable; requires minimal effort, time, or expense; and has an interoperable design and thorough privacy infrastructure. Similar features might be desirable for preventive health apps in other areas, paving the way for future discrete choice experiments. Nonetheless, to fully understand these preference dynamics, further qualitative or mixed method research on mobile self-monitoring-based sun protection and broader preventive mobile self-monitoring is required.International Registered Report Identifier (IRRID)RR2-10.2196/16087

Promoting family inclusive practice in home treatment teams

PurposeFamilies play an instrumental role in helping relatives experiencing mental health issues to stay well. In the context of wider initiatives promoting family and carer needs, this study aims to evaluate the feasibility, acceptability and potential benefits of bespoke training to develop clinicians’ skills in working with families in crisis.Design/methodology/approachThe study was an uncontrolled evaluation of a one-day workshop for home treatment team staff using pre- and post-questionnaires.FindingsIn total, 83 staff members participated. Overall, there was a strong agreement for the involvement of families, which increased marginally after training. There were significant changes in views about talking to family members without service user consent (p = 0.001) and keeping them informed of their relative’s well-being (p = 0.02). Qualitative feedback indicated that participants enjoyed the interactive elements, particularly role-playing. Training provided an opportunity to practice skills, share knowledge and facilitate the integration of family work into their professional role.Research limitations/implicationsConfident support for families contributes to effective mediation of crisis and continuation of care; factors important in reducing admission rates and protecting interpersonal relationships. Overall, the consistency of responses obtained from participants suggests that this workshop offers a helpful introduction to a family approach at times of a mental health crisis.Originality/valueThis pilot evaluation suggests this new one-day workshop, is a feasible and acceptable training program, which is beneficial in developing clinicians’ skills in working with families in a crisis.

A Survey on Phishing Detection and The Importance of Feature Selection In Data Mining Classification Algorithms

: In this era of Internet, the issue of security of information is at its peak. One of the main threats in this cyber world is phishing attacks which is an email or website fraud method that targets the genuine webpage or an email and hacks it without the consent of the end user. There are various techniques which help to classify whether the website or an email is legitimate or fake. The major contributors in the process of detection of these phishing frauds include the classification algorithms, feature selection techniques or dataset preparation methods and the feature extraction that plays an important role in detection as well as in prevention of these attacks. This Survey Paper studies the effect of all these contributors and the approaches that are applied in the study conducted on the recent papers. Some of the classification algorithms that are implemented includes Decision tree, Random Forest , Support Vector Machines, Logistic Regression , Lazy K Star, Naive Bayes and J48 etc.

Üniversite Kütüphanelerinde Kişisel Veriler: Ankara’daki 15 Üniversite Kütüphanesindeki Uygulamaların Analizi

Üniversite kütüphaneleri hizmet verdiği kullanıcı grubunun bilgi ihtiyaçlarının karşılanmasında sorumlulukları bulunan kurumlardır. Diğer kütüphane türlerinde olduğu gibi üniversite kütüphanelerinde de oluşturulan kullanıcı kayıtları bireyi tanımlayabilecek hatta bilgi arama davranışlarıyla da ilişkilendirilebilecek düzeyde kişisel verilerden oluşabilmektedir. Bu noktada üniversite kütüphanelerindeki kullanıcı verilerinin izinsiz ve yetkisiz kullanıma karşın korunması gerekliliği ortaya çıkmaktadır. Bu çalışmada, üniversite kütüphanelerinin kişisel verilerin korunmasına yönelik uygulamalarının betimlenmesi amaçlanmıştır. Belirlenen amaç çerçevesinde çalışmada öncelikle konuyla ilgili literatürden hareketle 15 üniversite kütüphanesindeki kişisel verilerin yönetimine dönük uygulamaları yöneticilerle yapılan görüşmelerle analiz edilmiştir. Bulgular, kütüphanelerde kayıt altına alınan kullanıcı verilerinin farklılık gösterdiğini ve kütüphanelerin yaklaşık yarısında kullanıcılardan kişisel verilerinin toplanmasına ve işlenmesine yönelik onaylarının alınmadığını ortaya koymuştur. Araştırmanın sonucunda, üniversite kütüphanelerinde kullanıcılara yönelik kişisel verilerin toplanması, kaydedilmesi, sınıflandırılması, işlenmesi, tutulması ve saklanması ve kullanıcılardan kişisel verilerin işlenmesine yönelik onaylarının alınması noktasında eksiklikler olduğu saptanmıştır.

Anonymous by design - [CrossTalk

THE INTERNET of Things has the potential to usher in many possibilities — including a surveillance state. In the July issue, I wrote about how user consent is an important prerequisite for companies building connected devices. But there are other ways companies are trying to ensure that connected devices don't invade people's privacy.

Data protection during the coronavirus crisis.

Smartphone apps to track SARS-CoV 2 infections need to fulfill certain minimal requirements to guarantee privacy and justify their use under data protection laws.

Developments in Privacy and Data Ownership in Mobile Health Technologies, 2016-2019.

Summary Objectives : To survey international regulatory frameworks that serve to protect privacy of personal data as a human right as well as to review the literature regarding privacy protections and data ownership in mobile health (mHealth) technologies between January 1, 2016 and June 1, 2019 in order to identify common themes. Methods : We performed a review of relevant literature available in English published between January 1, 2016 and June 1, 2019 from databases including PubMed, Google Scholar, and Web of Science, as well as relevant legislative background material. Articles out of scope (as detailed below) were eliminated. We categorized the remaining pool of articles and discrete themes were identified, specifically: concerns around data transmission and storage, including data ownership and the ability to re-identify previously de-identified data; issues with user consent (including the availability of appropriate privacy policies) and access control; and the changing culture and variable global attitudes toward privacy of health data. Results : Recent literature demonstrates that the security of mHealth data storage and transmission remains of wide concern, and aggregated data that were previously considered “de-identified” have now been demonstrated to be re-identifiable. Consumer-informed consent may be lacking with regard to mHealth applications due to the absence of a privacy policy and/or to text that is too complex and lengthy for most users to comprehend. The literature surveyed emphasizes improved access control strategies. This survey also illustrates a wide variety of global user perceptions regarding health data privacy. Conclusion : The international regulatory framework that serves to protect privacy of personal data as a human right is diverse. Given the challenges legislators face to keep up with rapidly advancing technology, we introduce the concept of a “healthcare fiduciary” to serve the best interest of data subjects in the current environment.

ICT Enabled Learning

Due to Covid -19 Pandemic educational institutions have closed in 107 countries affecting more than 860 million students. Information and communications technology have been widely adopted in most educational institutions in order to support e-learning through different learning methodologies. Information and communication technologies have changed the face of managing information in crisis, warning, impact and response. Information and communication technologies are changing the way that users are responding to environmental and health disruptions. In conflict zones it is dangerous for people to travel and maintain normal activities. However with mobile phones and internet applications and data on cloud, people can coordinate and communicate to help restore activities through negotiating travel, increasing situational awareness and conducting online social interaction. Security and compliances have become the key and mandatory for the organisation as data is growing in exponential form. Privacy laws applies not only to government operations but also to private enterprises and commercial transactions to understand how user data is being handled, processes to customer and visitor. It exploits to keep certain data confidential and if exposed it has to be with consent of user. Crisis management is designed to protect an organization and its stakeholders from threats and/or reduce the impact felt by threats. All the stages has discussed in detail along with diagram keeping concern in a crisis has to be public safety. A failure to address public safety intensifies the damage from a crisis. Reputation and financial concerns are considered after public safety has been remedied.

The internet of everything: implications of marketing analytics from a consumer policy perspective

PurposeThe purpose of this paper is to evaluate the impact of internet of everything (IoE) on marketing analytics, the benefits and challenges it presents and the implications of its policy and legal framework.Design/methodology/approachQualitative research methods are used across privacy statements and consumer social media data to determine factors of concern for business and consumers.FindingsThe qualitative analysis of privacy statements and consumer social media data unveils factors of concern that are common for businesses and consumers, such as user consent and data security, as well as problems specific to the IoE, including the use of mobile devices and various service providers. The study also shows a differentiation in the levels of information privacy concerns for marketing practice, the use of personal information, sharing information with third parties and consumer consent and agreement to critical terms.Practical implicationsRecommendations for policymakers, practitioners and researchers, especially concerning the need for more studies related to the issues of data security, information privacy and personal information are addressed.Originality/valueThere is a need to assess the potential implications that the use of marketing analytics in the IoE can have for marketing policy, governmental regulations and industry self-regulation. The purpose of this research is to perform an exploratory evaluation of the impact of IoE on marketing analytics, the benefits and challenges it presents and the implications of its policy and legal framework.