Privacy Apps for Smartphones: An Assessment of Users’ Preferences and Limitations

Sharma, Tanusree; Bashir, Masooda

doi:10.1007/978-3-030-50309-3_35

Cited by 6 publications

(3 citation statements)

References 28 publications

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“…user interface (UI) design(Alqahtani and Orji 2019;Sharma and Bashir 2020;Franzmann et al 2020) and capturing design rationale(Groen et al 2017;Kurtanović and Maalej 2017;Kurtanovic and Maalej 2018;Jha and Mahmoud 2019;Kunaefi and Aritsugi 2020).…”

mentioning

confidence: 99%

Analysing app reviews for software engineering: a systematic literature review

et al. 2022

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App reviews found in app stores can provide critically valuable information to help software engineers understand user requirements and to design, debug, and evolve software products. Over the last ten years, a vast amount of research has been produced to study what useful information might be found in app reviews, and how to mine and organise such information as efficiently as possible. This paper presents a comprehensive survey of this research, covering 182 papers published between 2012 and 2020. This survey classifies app review analysis not only in terms of mined information and applied data mining techniques but also, and most importantly, in terms of supported software engineering activities. The survey also reports on the quality and results of empirical evaluation of existing techniques and identifies important avenues for further research. This survey can be of interest to researchers and commercial organisations developing app review analysis techniques and to software engineers considering to use app review analysis.

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confidence: 99%

Analysing app reviews for software engineering: a systematic literature review

et al. 2022

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“…Attempts to understand the relationship between online reviews and downloads are not been made within a regulatory framework. The present study adds to the existing literature by providing a new view of the quality of apps that is linked directly to the user experience, which is mediated through online reviews and downloads [60]. The following objectives are proposed in order to achieve the general purpose of this study: (1) verify if there are any significant differences between certified and non-certified apps; and (2) determine if the apps' quality label affects the user experience, according to the type of applications (certified and non-certified).…”

Section: Online User Reviewsmentioning

confidence: 99%

Open Innovation in Digital Healthcare: Users’ Discrimination between Certified and Non-Certified mHealth Applications

Perera

Jiménez

Sancha

2020

Journal of Open Innovation: Technology, Market, and Complexity

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Mobile applications users consider it especially important to have quality certification, and particularly in an e-health context. However, if the app is certified, will user satisfaction be greater? This paper is intended to help answer that question. Therefore, with user satisfaction as a determinant of the quality of services, the purpose of the paper is to understand the extent to which certified and non-certified mHealth apps influence user experience. This was measured by online reviews and downloads. An empirical study was carried out with 50 mHealth apps (21 certified, 29 non-certified), which is a convenient sampling procedure. The Mahalanobis matching technique was used to test for significant differences between the groups. A comparative content analysis was performed on 6188 user comments and on app downloads. Non-parametric tests were preferred because the variables analyzed had a categorical structure. A log-linear model and advanced contingency tables were used to examine the more than two-way relationships of variables. The results show differences between the two samples (certified and non-certified mHealth apps). However, quality certification labels as a guarantee of the quality of apps do not have a modulating effect on the online reviews and downloads relationship. The model showed a statistically significant partial association between “certification” and “online user reviews” (Z = 2.174; sig = 0.042)] and between “download” and “online user reviews” (Z = 2.387; sig = 0.017).

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“…Several previous studies have shown the prevalence of smartphone privacy concerns and security threats around android permissions that can take place via privilege escalation attack that allows a malicious application to gain more capabilities leaked from a benign application [6], web API where message passing is also a medium of attack surface while providing availing inter-application collaboration. Adversarial can sniff, modify, steal or replace content with compromising user privacy [7], [19]. Again, malicious application can inject malicious messages/code which can lead to users' data breaches.…”

Section: Introductionmentioning

confidence: 99%

Mapping Risk Assessment Strategy for COVID-19 Mobile Apps’ Vulnerabilities

Sharma

Dyer

Campbell

et al. 2021

Lecture Notes in Networks and Systems

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Recent innovations in mobile technologies are playing an important and vital role in combating the COVID-19 pandemic. While mobile apps' functionality plays a crucial role in tackling the COVID-19 spread, it is also raising concerns about the associated privacy risks that users may face. Recent research studies have showed various technological measures on mobile applications that lack consideration of privacy risks in their data practices. For example, security vulnerabilities in COVID-19 apps can be exploited and therefore also pose privacy violations. In this paper, we focus on recent and newly developed COVID-19 apps and consider their threat landscape. Our objective was to identify security vulnerabilities that can lead to user-level privacy risks. We also formalize our approach by measuring the level of risk associated with assets and services that attackers may be targeting to capture during the exploitation. We utilized baseline risk assessment criteria within the scope of three specific security vulnerabilities that often exists in COVID-19 applications namely credential leaks, insecure communication, and HTTP request libraries. We present a proof of concept implementation for risk assessment of COVID-19 apps that can be utilized to evaluate privacy risk by the impact of assets and threat likelihood.

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Privacy Apps for Smartphones: An Assessment of Users’ Preferences and Limitations

Cited by 6 publications

References 28 publications

Analysing app reviews for software engineering: a systematic literature review

Analysing app reviews for software engineering: a systematic literature review

Open Innovation in Digital Healthcare: Users’ Discrimination between Certified and Non-Certified mHealth Applications

Mapping Risk Assessment Strategy for COVID-19 Mobile Apps’ Vulnerabilities

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