scholarly journals Using a web scraper to assess the level of privacy of diabetes mobile applications (Preprint)

2019 ◽  
Author(s):  
José Javier Flors-Sidro ◽  
Mowafa Househ ◽  
Alaa Abd-Alrazaq ◽  
Josep Vidal-Alaball ◽  
Luis Fernandez-Luque ◽  
...  
Keyword(s):  
Data Protection ◽  
Mobile Applications ◽  
Data Privacy ◽  
Mobile Apps ◽  
Significant Risk ◽  
Android Apps ◽  
Related Information ◽  
Actual Compliance ◽  
Private Data ◽  
Regulatory Bodies

BACKGROUND Mobile health has become a major channel for the support of people living with diabetes. Accordingly, the availability of diabetes mobile apps has been steadily increasing. Most of the previous reviews of diabetes apps have focused on the apps’ features and their alignment with clinical guidelines. However, there is a lack of knowledge on the actual compliance of diabetes apps with privacy and data security aspects. OBJECTIVE The aim of this study was to assess the level of privacy of diabetes mobile applications to contribute to raising the awareness of final users, developers and data-protection governmental regulators towards privacy issues. METHODS A web scraper capable of retrieving Android apps’ privacy-related information, particularly the dangerous permissions required by the apps, was developed with the aim of analyzing privacy aspects related to diabetes apps. Following the research selection criteria, the original 882 apps were narrowed down to 497 apps, which were finally included in the analysis. RESULTS 60% of diabetes apps may request dangerous permissions, which poses a significant risk for the users’ data privacy. In addition, 30% of the apps do not return their privacy policy website. Moreover, it was found that 40% of apps contain advertising, and that some apps that declared not to contain it actually had ads. 95.4% of the apps were free of cost, and those belonging to the Medical and Health and Fitness categories were the most popular. However, final users do not always realize that the free-apps’ business model is largely based on advertising, and consequently, on sharing or selling their private data, either directly or indirectly, to unknown third-parties. CONCLUSIONS The aforementioned findings unquestionably confirm the necessity to educate users and raise their awareness regarding diabetes apps privacy aspects. For this purpose, this research recommends properly and comprehensively training users, ensuring that governments and regulatory bodies enforce strict data protection laws, devising much tougher security policies and protocols in Android and in the Google Play Store, and the implication and supervision of all stakeholders in the apps’ development process.

How Do Mobile Applications for Cancer Communicate About Their Privacy Practices?

2021 ◽  
pp. 113-144
Author(s):  
Zerin Mahzabin Khan ◽  
Rukhsana Ahmed ◽  
Devjani Sen
Keyword(s):  
Mobile Applications ◽  
Critical Analysis ◽  
Data Privacy ◽  
Mobile Apps ◽  
Personal Data ◽  
End Users ◽  
Privacy Policies ◽  
Inadequate Information ◽  
Practical Implications ◽  
Complex Manner

No previous research on cancer mobile applications (apps) has investigated issues associated with the data privacy of its consumers. The current chapter addressed this gap in the literature by assessing the content of online privacy policies of selected cancer mobile apps through applying a checklist and performing an in-depth critical analysis to determine how the apps communicated their privacy practices to end users. The results revealed that the privacy policies were mostly ambiguous, with content often presented in a complex manner and inadequate information on the ownership, use, disclosure, retention, and collection of end users' personal data. These results highlight the importance of improving the transparency of privacy practices in health and fitness cancer mobile apps to clearly and effectively communicate how end users' personal data are collected, stored, and shared. The chapter concludes with recommendations and discussion on practical implications for stakeholders like cancer app users, developers, policymakers, and clinicians.

scholarly journals CAP-A: A Suite of Tools for Data Privacy Evaluation of Mobile Applications

2020 ◽  
Author(s):  
Ioannis Chrysakis ◽  
Giorgos Flouris ◽  
George Ioannidis ◽  
Maria Makridaki ◽  
Theodore Patkos ◽  
...  
Keyword(s):  
Mobile Applications ◽  
Data Privacy ◽  
Mobile Apps ◽  
Personal Data ◽  
Privacy Policy ◽  
Policy Makers ◽  
Policy Documents ◽  
The Public

The utilisation of personal data by mobile apps is often hidden behind vague Privacy Policy documents, which are typically lengthy, difficult to read (containing legal terms and definitions) and frequently changing. This paper discusses a suite of tools developed in the context of the CAP-A project, aiming to harness the collective power of users to improve their privacy awareness and to promote privacy-friendly behaviour by mobile apps. Through crowdsourcing techniques, users can evaluate the privacy friendliness of apps, annotate and understand Privacy Policy documents, and help other users become aware of privacy-related aspects of mobile apps and their implications, whereas developers and policy makers can identify trends and the general stance of the public in privacy-related matters. The tools are available for public use in: https://cap-a.eu/tools/.

How Do Mobile Applications for Cancer Communicate About Their Privacy Practices?

2021 ◽  
pp. 667-691
Author(s):  
Zerin Mahzabin Khan ◽  
Rukhsana Ahmed ◽  
Devjani Sen
Keyword(s):  
Mobile Applications ◽  
Critical Analysis ◽  
Data Privacy ◽  
Mobile Apps ◽  
Personal Data ◽  
End Users ◽  
Privacy Policies ◽  
Inadequate Information ◽  
Practical Implications ◽  
Complex Manner

No previous research on cancer mobile applications (apps) has investigated issues associated with the data privacy of its consumers. The current chapter addressed this gap in the literature by assessing the content of online privacy policies of selected cancer mobile apps through applying a checklist and performing an in-depth critical analysis to determine how the apps communicated their privacy practices to end users. The results revealed that the privacy policies were mostly ambiguous, with content often presented in a complex manner and inadequate information on the ownership, use, disclosure, retention, and collection of end users' personal data. These results highlight the importance of improving the transparency of privacy practices in health and fitness cancer mobile apps to clearly and effectively communicate how end users' personal data are collected, stored, and shared. The chapter concludes with recommendations and discussion on practical implications for stakeholders like cancer app users, developers, policymakers, and clinicians.

scholarly journals Automated Bidirectional Languages Localization Testing for Android Apps with Rich GUI

2016 ◽  
Vol 2016 ◽  
pp. 1-13 ◽  
Author(s):  
Aiman M. Ayyal Awwad ◽  
Wolfgang Slany
Keyword(s):  
Mobile Applications ◽  
Mobile Apps ◽  
Arabic Language ◽  
Automatic Testing ◽  
High Quality ◽  
Android Apps ◽  
Culturally Congruent ◽  
Android Applications

Mobile apps are everywhere. The release of apps on a worldwide scale requires them to be made available in many languages, including bidirectional languages. Developers and translators are usually different persons. While automatic testing by itself is important in general in order to be able to develop high quality software, such automatic tests become absolutely essential when developers that do not possess enough knowledge about right-to-left languages need to maintain code that is written for bidirectional languages. A few bidirectional localization tests of mobile applications exist. However, their functionality is limited since they only cover translations and adoption of locales. In this paper we present our approach for automating the bidirectional localization testing for Android applications with a complete consideration for BiDi-languages issues. The objective is to check for any localization defects in the product. The proposed methods are used to test issues of bidirectional apps in general and specifically for the Arabic language. The results show that the methods are able to effectively reveal deficiencies in the app’s design, ensure that the localized app matches all expectations of local users, and guarantee that the product is culturally congruent to local conventions.

scholarly journals User Privacy and Data Flow Control for Android Apps: Systematic Literature Review

2021 ◽  
Author(s):  
Zainab Rashid Alkindi ◽  
Mohamed Sarrab ◽  
Nasser Alzeidi
Keyword(s):  
Literature Review ◽  
Flow Control ◽  
Systematic Literature Review ◽  
Data Privacy ◽  
Data Flow ◽  
Mobile Apps ◽  
Relevant Literature ◽  
User Privacy ◽  
Android Apps ◽  
Data Flow Control

Android mobile apps gain access to numerous users’ private data. Users of different Android mobile apps have less control over their sensitive data during their installation and run-time. Too often, these apps consider data privacy less serious than users’ expectations. Many mobile apps misbehave and upload users’ data without permission which confirmed the possibility of privacy leakage through different network channels. The literature has proposed various approaches to protect user’s data and avoid privacy violations. In this paper, we provide a comprehensive overview of state-of-art research on Android user privacy, and data flow control. the aim is to highlight the main trends, pinpoint the main methodologies applied, and enumerate the privacy violations faced by Android users. We also shed some light on the directions where the researcher’s community effort is still needed. To this end, we conduct a Systematic Literature Review (SLR) during which we surveyed 114 relevant research papers published in leading conferences and journals. Our thorough examination of the relevant literature has led to a critical analysis of the proposed solutions with a focus on user privacy extensions and mechanism for the Android mobile platform. Furthermore, possible solutions and research directions have been discussed.    

scholarly journals Evaluating the Data Privacy of Mobile Applications Through Crowdsourcing

2020 ◽  
Author(s):  
Ioannis Chrysakis ◽  
Giorgos Flouris ◽  
George Ioannidis ◽  
Maria Makridaki ◽  
Theodore Patkos ◽  
...  
Keyword(s):  
Mobile Applications ◽  
Data Privacy ◽  
Collective Intelligence ◽  
Mobile Apps ◽  
Mobile App ◽  
Smart Devices ◽  
Privacy Policy ◽  
Policy Documents ◽  
Privacy Concerns

Consumers are largely unaware regarding the use being made to the data that they generate through smart devices, or their GDPR-compliance, since such information is typically hidden behind vague privacy policy documents, which are often lengthy, difficult to read (containing legal terms and definitions) and frequently changing. This paper describes the activities of the CAP-A project, whose aim is to apply crowdsourcing techniques to evaluate the privacy friendliness of apps, and to allow users to better understand the content of Privacy Policy documents and, consequently, the privacy implications of using any given mobile app. To achieve this, we developed a set of tools that aim at assisting users to express their own privacy concerns and expectations and assess the mobile apps’ privacy properties through collective intelligence.

How Do Mobile Applications for Cancer Communicate About Their Privacy Practices?

2021 ◽  
pp. 1929-1953
Author(s):  
Zerin Mahzabin Khan ◽  
Rukhsana Ahmed ◽  
Devjani Sen
Keyword(s):  
Mobile Applications ◽  
Critical Analysis ◽  
Data Privacy ◽  
Mobile Apps ◽  
Personal Data ◽  
End Users ◽  
Privacy Policies ◽  
Inadequate Information ◽  
Practical Implications ◽  
Complex Manner

No previous research on cancer mobile applications (apps) has investigated issues associated with the data privacy of its consumers. The current chapter addressed this gap in the literature by assessing the content of online privacy policies of selected cancer mobile apps through applying a checklist and performing an in-depth critical analysis to determine how the apps communicated their privacy practices to end users. The results revealed that the privacy policies were mostly ambiguous, with content often presented in a complex manner and inadequate information on the ownership, use, disclosure, retention, and collection of end users' personal data. These results highlight the importance of improving the transparency of privacy practices in health and fitness cancer mobile apps to clearly and effectively communicate how end users' personal data are collected, stored, and shared. The chapter concludes with recommendations and discussion on practical implications for stakeholders like cancer app users, developers, policymakers, and clinicians.

Privacy-preserving Collaborative Training for Medical Image Analysis Based on Multi-Blockchain

2020 ◽  
Vol 23 ◽  
Author(s):  
Wanlu Zhang ◽  
Qigang Wang ◽  
Mei Li
Keyword(s):  
Medical Image ◽  
Data Privacy ◽  
Medical Image Analysis ◽  
Auxiliary Information ◽  
Training Process ◽  
Private Data ◽  
Medical Institutions ◽  
Model Training ◽  
Collaborative Training ◽  
Similar Task

Background: As artificial intelligence and big data analysis develop rapidly, data privacy, especially patient medical data privacy, is getting more and more attention. Objective: To strengthen the protection of private data while ensuring the model training process, this article introduces a multi-Blockchain-based decentralized collaborative machine learning training method for medical image analysis. In this way, researchers from different medical institutions are able to collaborate to train models without exchanging sensitive patient data. Method: Partial parameter update method is applied to prevent indirect privacy leakage during model propagation. With the peer-to-peer communication in the multi-Blockchain system, a machine learning task can leverage auxiliary information from another similar task in another Blockchain. In addition, after the collaborative training process, personalized models of different medical institutions will be trained. Results: The experimental results show that our method achieves similar performance with the centralized model-training method by collecting data sets of all participants and prevents private data leakage at the same time. Transferring auxiliary information from similar task on another Blockchain has also been proven to effectively accelerate model convergence and improve model accuracy, especially in the scenario of absence of data. Personalization training process further improves model performance. Conclusion: Our approach can effectively help researchers from different organizations to achieve collaborative training without disclosing their private data.

Mobile Applications for Health Management of Older Adults: A Scoping Review (Preprint)

2020 ◽  
Author(s):  
Nurul Asilah Ahmad ◽  
Shahrul Azman Mohd Noah ◽  
Arimi Fitri Mat Ludin ◽  
Suzana Shahar ◽  
Noorlaili Mohd Tohit
Keyword(s):  
Older Adults ◽  
Goal Setting ◽  
Mobile Applications ◽  
Health Management ◽  
Mobile Apps ◽  
Personalized Feedback ◽  
Self Monitoring ◽  
App Store ◽  
Evidenced Based ◽  
Google Play

BACKGROUND Currently, the use of smartphones to deliver health-related content has experienced a rapid growth, with more than 165,000 mobile health (mHealth) applications currently available in the digital marketplace such as iOS store and Google Play. Among these, there are several mobile applications (mobile apps) that offer tools for disease prevention and management among older generations. These mobile apps could potentially promote health behaviors which will reduce or delay the onset of disease. However, no review to date that has focused on the app marketplace specific for older adults and little is known regarding its evidence-based quality towards the health of older adults. OBJECTIVE The aim of this review was to characterize and critically appraise the content and functionality of mobile apps that focuses on health management and/or healthy lifestyle among older adults. METHODS An electronic search was conducted between May 2019 to December 2019 of the official app store for two major smartphone operating systems: iPhone operating system (iTunes App Store) and Android (Google Play Store). Stores were searched separately using predetermined search terms. Two authors screened apps based on information provided in the app description. Metadata from all included apps were abstracted into a standard assessment criteria form. Evidenced based strategies and health care expert involvement of included apps was assessed. Evidenced based strategies included: self-monitoring, goal setting, physical activity support, healthy eating support, weight and/or health assessment, personalized feedback, motivational strategies, cognitive training and social support. Two authors verified the data with reference to the apps and downloaded app themselves. RESULTS A total of 16 apps met the inclusion criteria. Six out of 16 (37.5%) apps were designed exclusively for the iOS platform while ten out of 16 (62.5%) were designed for Android platform exclusively. Physical activity component was the most common feature offered in all the apps (9/16, 56.3%) and followed by cognitive training (8/16, 50.0%). Diet/nutrition (0/16, 0%) feature, however, was not offered on all reviewed mobile apps. Of reviewed apps, 56.3% (9/16) provide education, 37.5% (6/16) provide self-monitoring features, 18.8% (3/16) provide goal setting features, 18.5% (3/16) provide personalized feedback, 6.3% (1/16) provide social support and none of the reviewed apps offers heart rate monitoring and reminder features to the users. CONCLUSIONS All reviewed mobile apps for older adults in managing health did not focused on diet/nutrition component, lack of functional components and lack of health care professional involvement in their development process. There is also a need to carry out scientific testing prior to the development of the app to ensure cost effective and its health benefits to older adults. Collaborative efforts between developers, researchers, health professionals and patients are needed in developing evidence-based, high quality mobile apps in managing health prior they are made available in the app store.

Assessment and Prediction of Privacy Concerns on Health Apps (Preprint)

2020 ◽  
Author(s):  
Reham AlTamime ◽  
Vincent Marmion ◽  
Wendy Hall
Keyword(s):  
Data Sharing ◽  
Mobile Applications ◽  
Retention Rate ◽  
Mobile Apps ◽  
Third Party ◽  
Privacy Concerns ◽  
Health Apps ◽  
Mobile Health Apps ◽  
Specific Factors ◽  
And Control

BACKGROUND Mobile apps and IoT-enabled smartphones technologies facilitate collecting, sharing, and inferring from a vast amount of data about individuals’ location, health conditions, mobility status, and other factors. The use of such technology highlights the importance of understanding individuals’ privacy concerns to design applications that integrate their privacy expectations and requirements. OBJECTIVE This paper explores, assesses, and predicts individuals’ privacy concerns in relation to collecting and disclosing data on mobile health apps. METHODS We designed a questionnaire to identify participants’ privacy concerns pertaining to a set of 432 mobile apps’ data collection and sharing scenarios. Participants were presented with 27 scenarios that varied across three categorical factors: (1) type of data collected (e.g. health, demographic, behavioral, and location); (2) data sharing (e.g., whether it is shared, and for what purpose); and, (3) retention rate (e.g., forever, until the purpose is satisfied, unspecified, week, or year). RESULTS Our findings show that type of data, data sharing, and retention rate are all factors that affect individuals’ privacy concerns. However, specific factors such as collecting and disclosing health data to a third-party tracker play a larger role than other factors in triggering privacy concerns. CONCLUSIONS Our findings suggest that it is possible to predict privacy concerns based on these three factors. We propose design approaches that can improve users’ awareness and control of their data on mobile applications

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