iOS

Jakob Ohme, Theo B. Araujo, Claes H. de Vreese, J. T. Piotrowski

With digital communication increasingly shifting to mobile devices, communication research needs to explore ways to retrieve, process, and analyze digital trace data on people’s most personal devices. This study presents a new methodological approach, mobile data donations, in which smartphone usage data is collected unobtrusively with the help of mobile log data. The iOS Screen Time function is used as a test case for gathering log data with the help of screenshots. The study investigates the feasibility of the method, sample biases, and accuracy of smartphone usage self-reports on a general population sample of Dutch citizens (n=404). Importantly, it explores how mobile data donations can be used as add-ons or substitutes for conventional media exposure measures. Results indicate that (a) users’ privacy concerns and technical skills are crucial factors for the willingness to donate mobile log data and (b) there is a strong tendency for underreporting of smartphone usage duration and frequency.

Konrad Kollnig, A. Shuba, M. V. Kleek, Reuben Binns, N. Shadbolt

Tracking is a highly privacy-invasive data collection practice that has been ubiquitous in mobile apps for many years due to its role in supporting advertising-based revenue models. In response, Apple introduced two significant changes with iOS 14: App Tracking Transparency (ATT), a mandatory opt-in system for enabling tracking on iOS, and Privacy Nutrition Labels, which disclose what kinds of data each app processes. So far, the impact of these changes on individual privacy and control has not been well understood. This paper addresses this gap by analysing two versions of 1,759 iOS apps from the UK App Store: one version from before iOS 14 and one that has been updated to comply with the new rules. We find that Apple’s new policies, as promised, prevent the collection of the Identifier for Advertisers (IDFA), an identifier for cross-app tracking. Smaller data brokers that engage in invasive data practices will now face higher challenges in tracking users – a positive development for privacy. However, the number of tracking libraries has – on average – roughly stayed the same in the studied apps. Many apps still collect device information that can be used to track users at a group level (cohort tracking) or identify individuals probabilistically (fingerprinting). We find real-world evidence of apps computing and agreeing on a fingerprinting-derived identifier through the use of server-side code, thereby violating Apple’s policies. We find that Apple itself engages in some forms of tracking and exempts invasive data practices like first-party tracking and credit scoring from its new tracking rules. We also find that the new Privacy Nutrition Labels are sometimes inaccurate and misleading, especially in less popular apps. Overall, our observations suggest that, while Apple’s changes make tracking individual users more difficult, they motivate a countermovement, and reinforce existing market power of gatekeeper companies with access to large troves of first-party data. Making the privacy properties of apps transparent through large-scale analysis remains a difficult target for independent researchers, and a key obstacle to meaningful, accountable and verifiable privacy protections.

Shikun Zhang, Yuanyuan Feng, Yaxing Yao, L. Cranor, N. Sadeh

Standardized privacy labels that succinctly summarize those data practices that people are most commonly concerned about offer the promise of providing users with more effective privacy notices than full-length privacy policies. With their introduction by Apple in iOS 14 and Google’s recent adoption in its Play Store, mobile app privacy labels are for the first time available at scale to users. We report the first indepth interview study with 24 lay iPhone users to investigate their experiences, understanding, and perceptions of Apple’s privacy labels. We uncovered misunderstandings of and dissatisfaction with the iOS privacy labels that hinder their effectiveness, including confusing structure, unfamiliar terms, and disconnection from permission settings and controls. We identify areas where app privacy labels might be improved and propose suggestions to address shortcomings to make them more understandable, usable, and useful.

F. R. Ghadi, Masoud Kaveh, Diego Martín

In this article, we explore the communication performance of vehicle-to-vehicle (V2V) networks assisted by a reconfigurable intelligent surface (RIS) and a simultaneous transmitting and reflecting intelligent omni-surface (STAR-IOS) under non-orthogonal multiple access (NOMA) and orthogonal multiple access (OMA) schemes. In particular, we consider that the RIS is close to the transmitter vehicle while the STAR-IOS is near the receiver vehicles. In addition, it is assumed that the STAR-IOS exploits the energy-splitting (ES) protocol for communication and the fading channels between the RIS and STAR-IOS follow composite Fisher-Snedecor $\mathcal {F}$ distribution. Under such assumptions, we first use the central limit theorem (CLT) to derive the PDF and the CDF of equivalent channels at receiver vehicles, and then, we derive the closed-form expression of outage probability (OP) under NOMA/OMA scenarios. Additionally, by exploiting Jensen's inequality, we propose an upper bound of the ergodic capacity (EC) and subsequently develop an analytical expression of the energy efficiency (EE) for both NOMA and OMA cases. Further, our analytical results, which are double-checked with the Monte-Carlo simulation, reveal that applying RIS/STAR-RIS in V2V communications significantly enhances the communication performance of intelligent transportation systems (ITS). Besides, the results indicate that considering the NOMA scheme provides better performance in terms of the OP, EC, and EE as compared with the OMA case for the considered V2V communication system.

Michael Klein, Frank J. Tuminelli, A. Sallustio, Graziano D. Giglio, Henriette Lerner, Robert W. Berg, Allon Waltuch

OBJECTIVES Report the results with a novel workflow of digital restoration for completely edentulous patients with implant supported full arch fixed dental prostheses (ISFDP). METHODS This multicenter retrospective clinical study was based on the evaluation from a cohort of 29 patients restored with 37 ISFDP's designed and manufactured from the data captured by a direct intraoral scan, using a novel full digital system (NEXUS IOS®, Osteon Medical, a Keystone Dental Group company, Melbourne, Australia). Data was collected over a 3-year period, in seven different dental centers. This study reported on the clinical parameters including: precision of marginal fit, functional and esthetic integration of Nexus ISFDP's. All patients were followed for a period of one year post delivery. Implant survival, biologic and prosthetic complications were assessed, at one year. A statistical analysis was conducted. RESULTS All 37 ISFDP's were deemed clinically acceptable on insertion. Implant survival at one year was 100%. The biologic and prosthetic complications were minimal during the follow-up period. CONCLUSIONS ISFDP's, designed and manufactured using the NEXUS IOS® system, are clinically acceptable, with a low incidence of complications at one year. Long-term clinical studies are needed. STATEMENT OF CLINICAL RELEVANCE Within the limitations of this study (retrospective design, small patient sample, limited follow-up) the NEXUS IOS® system seems to represent a viable solution for the restoration of completely edentulous patients with ISFDP, in a full digital workflow.