Mobile Privacy and Business-to-Platform Dependencies: An Analysis of SEC Disclosures

This Article systematically examines the dependence of mobile apps on mobile platforms for the collection and use of personal information through an analysis of Securities and Exchange Commission (SEC) filings of mobile app companies. The Article uses these disclosures to find systematic evidence of how app business models are shaped by the governance of user data by mobile platforms, in order to reflect on the role of platforms in privacy regulation more generally. The analysis of SEC filings documented in the Article produces new and unique insights into the data practices and data-related aspects of the business models of popular mobile apps and shows the value of SEC filings for privacy law and policy research more generally. The discussion of SEC filings and privacy builds on regulatory developments in SEC disclosures and cybersecurity of the last decade. The Article also connects to recent regulatory developments in the U.S. and Europe, including the General Data Protection Regulation, the proposals for a new ePrivacy Regulation and a Regulation of fairness in business-to-platform relations

InShopnito: an advanced yet privacy-friendly mobile shopping application

Mobile Shopping Applications (MSAs) are rapidly gaining popularity. They enhance the shopping experience, by offering customized recommendations or incorporating customer loyalty programs. Although MSAs are quite effective at attracting new customers and binding existing ones to a retailer's services, existing MSAs have several shortcomings. The data collection practices involved in MSAs and the lack of transparency thereof are important concerns for many customers. This paper presents inShopnito, a privacy-preserving mobile shopping application. All transactions made in inShopnito are unlinkable and anonymous. However, the system still offers the expected features from a modern MSA. Customers can take part in loyalty programs and earn or spend loyalty points and electronic vouchers. Furthermore, the MSA can suggest personalized recommendations even though the retailer cannot construct rich customer profiles. These profiles are managed on the smartphone and can be partially disclosed in order to get better, customized recommendations. Finally, we present an implementation called inShopnito, of which the security and performance is analyzed. In doing so, we show that it is possible to have a privacy-preserving MSA without having to sacrifice practicality

Development and Analysis of a Unified Mobile App for Coffee Shop Operations and Ordering Experience: A Proposal Review

This study extends the exploration of ordering apps in the context of coffee shop owners, specifically focusing on the utilization of popular apps like Grabfood and Foodpanda. With the increasing number of coffee shops adopting ordering apps, there arises a clear necessity for a coffee-focused app that can effectively address the unique demands of establishments. The objective of this study is to conduct a comprehensive review of a mobile app specifically designed to streamline the process of ordering coffee in advance, with a paramount emphasis on ensuring its reliability. By developing an app that caters to the specific needs of coffee shops, both owners and customers can benefit greatly. The app will serve as a dedicated platform, connecting coffee enthusiasts with quality coffee shops, while offering a seamless and convenient ordering experience. By providing a high-quality ordering system that encompasses the full range of customization options for beverages, the developed app is expected to significantly enhance the customer experience and ultimately boost sales for the coffee establishments listed on the platform. With a focus on reliability, the app will enable coffee shop owners to efficiently manage orders, minimize errors, and improve overall operational efficiency. Moreover, by fostering a user-friendly interface and intuitive design, the app will engage customers and encourage them to explore new coffee shops, further promoting the growth of the coffee industry. This study will contribute to the existing body of knowledge by highlighting the importance of tailored ordering apps for coffee shops and providing insights into the development and implementation of such apps. The findings will be valuable not only for coffee shop owners seeking to enhance their business operations but also for app developers looking to cater to the specific needs of the coffee industry. Ultimately, the study aims to bridge the gap between technology and the coffee business, fostering innovation and growth in the ever-evolving digital landscape

Context-Awareness in Android Application: Context-Aware Personal Financial Assistance (CAPFA)

This report describes system that examines and reacts to an individual's changing context which can be computer context, user context, or physical context. The author defines mobile computing, context-awareness and financial goals. Integration between these three concept leads to the idea of developing Context-Aware Personal Financial Assistance (CAPFA). This report summarizes the reasons why people fail to achieve their financial goal(s) and how the proposed solution, CAPFA can helps to minimize the rate of failure. CAPFA, an Android context-aware application supports users in managing their financial goal(s). It ensures that user will commit to the financial goal(s) set. The objectives of developing CAPFA are to study how context-aware can be applied in personal financial assistance tool and to develop a context-aware personal financial assistance tool for assisting user in achieving financial goal(s). Software Engineering Process will be the project development guidance from the very beginning to the very end of developing CAPF A. This report describes the hardware and software used, architecture implemented, and functions available

Cloud/fog computing resource management and pricing for blockchain networks

The mining process in blockchain requires solving a proof-of-work puzzle, which is resource expensive to implement in mobile devices due to the high computing power and energy needed. In this paper, we, for the first time, consider edge computing as an enabler for mobile blockchain. In particular, we study edge computing resource management and pricing to support mobile blockchain applications in which the mining process of miners can be offloaded to an edge computing service provider. We formulate a two-stage Stackelberg game to jointly maximize the profit of the edge computing service provider and the individual utilities of the miners. In the first stage, the service provider sets the price of edge computing nodes. In the second stage, the miners decide on the service demand to purchase based on the observed prices. We apply the backward induction to analyze the sub-game perfect equilibrium in each stage for both uniform and discriminatory pricing schemes. For the uniform pricing where the same price is applied to all miners, the existence and uniqueness of Stackelberg equilibrium are validated by identifying the best response strategies of the miners. For the discriminatory pricing where the different prices are applied to different miners, the Stackelberg equilibrium is proved to exist and be unique by capitalizing on the Variational Inequality theory. Further, the real experimental results are employed to justify our proposed model.Comment: 16 pages, double-column version, accepted by IEEE Internet of Things Journa