28,237 research outputs found
Context Data Categories and Privacy Model for Mobile Data Collection Apps
Context-aware applications stemming from diverse fields like mobile health,
recommender systems, and mobile commerce potentially benefit from knowing
aspects of the user's personality. As filling out personality questionnaires is
tedious, we propose the prediction of the user's personality from smartphone
sensor and usage data. In order to collect data for researching the
relationship between smartphone data and personality, we developed the Android
app TYDR (Track Your Daily Routine) which tracks smartphone data and utilizes
psychometric personality questionnaires. With TYDR, we track a larger variety
of smartphone data than similar existing apps, including metadata on
notifications, photos taken, and music played back by the user. For the
development of TYDR, we introduce a general context data model consisting of
four categories that focus on the user's different types of interactions with
the smartphone: physical conditions and activity, device status and usage, core
functions usage, and app usage. On top of this, we develop the privacy model
PM-MoDaC specifically for apps related to the collection of mobile data,
consisting of nine proposed privacy measures. We present the implementation of
all of those measures in TYDR. Although the utilization of the user's
personality based on the usage of his or her smartphone is a challenging
endeavor, it seems to be a promising approach for various types of
context-aware mobile applications.Comment: Accepted for publication at the 15th International Conference on
Mobile Systems and Pervasive Computing (MobiSPC 2018
Third Party Tracking in the Mobile Ecosystem
Third party tracking allows companies to identify users and track their
behaviour across multiple digital services. This paper presents an empirical
study of the prevalence of third-party trackers on 959,000 apps from the US and
UK Google Play stores. We find that most apps contain third party tracking, and
the distribution of trackers is long-tailed with several highly dominant
trackers accounting for a large portion of the coverage. The extent of tracking
also differs between categories of apps; in particular, news apps and apps
targeted at children appear to be amongst the worst in terms of the number of
third party trackers associated with them. Third party tracking is also
revealed to be a highly trans-national phenomenon, with many trackers operating
in jurisdictions outside the EU. Based on these findings, we draw out some
significant legal compliance challenges facing the tracking industry.Comment: Corrected missing company info (Linkedin owned by Microsoft). Figures
for Microsoft and Linkedin re-calculated and added to Table
Money Walks: A Human-Centric Study on the Economics of Personal Mobile Data
In the context of a myriad of mobile apps which collect personally
identifiable information (PII) and a prospective market place of personal data,
we investigate a user-centric monetary valuation of mobile PII. During a 6-week
long user study in a living lab deployment with 60 participants, we collected
their daily valuations of 4 categories of mobile PII (communication, e.g.
phonecalls made/received, applications, e.g. time spent on different apps,
location and media, photos taken) at three levels of complexity (individual
data points, aggregated statistics and processed, i.e. meaningful
interpretations of the data). In order to obtain honest valuations, we employ a
reverse second price auction mechanism. Our findings show that the most
sensitive and valued category of personal information is location. We report
statistically significant associations between actual mobile usage, personal
dispositions, and bidding behavior. Finally, we outline key implications for
the design of mobile services and future markets of personal data.Comment: 15 pages, 2 figures. To appear in ACM International Joint Conference
on Pervasive and Ubiquitous Computing (Ubicomp 2014
After Over-Privileged Permissions: Using Technology and Design to Create Legal Compliance
Consumers in the mobile ecosystem can putatively protect their privacy with the use of application permissions. However, this requires the mobile device owners to understand permissions and their privacy implications. Yet, few consumers appreciate the nature of permissions within the mobile ecosystem, often failing to appreciate the privacy permissions that are altered when updating an app. Even more concerning is the lack of understanding of the wide use of third-party libraries, most which are installed with automatic permissions, that is permissions that must be granted to allow the application to function appropriately. Unsurprisingly, many of these third-party permissions violate consumers’ privacy expectations and thereby, become “over-privileged” to the user. Consequently, an obscurity of privacy expectations between what is practiced by the private sector and what is deemed appropriate by the public sector is exhibited. Despite the growing attention given to privacy in the mobile ecosystem, legal literature has largely ignored the implications of mobile permissions. This article seeks to address this omission by analyzing the impacts of mobile permissions and the privacy harms experienced by consumers of mobile applications. The authors call for the review of industry self-regulation and the overreliance upon simple notice and consent. Instead, the authors set out a plan for greater attention to be paid to socio-technical solutions, focusing on better privacy protections and technology embedded within the automatic permission-based application ecosystem
Big Brother is Listening to You: Digital Eavesdropping in the Advertising Industry
In the Digital Age, information is more accessible than ever. Unfortunately, that accessibility has come at the expense of privacy. Now, more and more personal information is in the hands of corporations and governments, for uses not known to the average consumer. Although these entities have long been able to keep tabs on individuals, with the advent of virtual assistants and “always-listening” technologies, the ease by which a third party may extract information from a consumer has only increased. The stark reality is that lawmakers have left the American public behind. While other countries have enacted consumer privacy protections, the United States has no satisfactory legal framework in place to curb data collection by greedy businesses or to regulate how those companies may use and protect consumer data. This Article contemplates one use of that data: digital advertising. Inspired by stories of suspiciously well-targeted advertisements appearing on social media websites, this Article additionally questions whether companies have been honest about their collection of audio data. To address the potential harms consumers may suffer as a result of this deficient privacy protection, this Article proposes a framework wherein companies must acquire users\u27 consent and the government must ensure that businesses do not use consumer information for harmful purposes
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