The Smartphone App Economy and App Ecosystems

This chapter gives an overview of the smartphone app economy and its various constituent ecosystems. It examines the role of the app store model and the proliferation of mobile apps in the shift from value chains controlled by network operators and handset manufacturers, to value networks – or ecosystems – focused around operating systems and apps. It outlines some of the benefits and disadvantages for developers of the app store model for remuneration and distribution. The chapter concludes with a discussion of recent research on the size and employment effects of the app economy.

Evaluation of Machine Learning Classifiers for Mobile Network Intrusion Detection Systems

Mobile malwares are increasing with the growing number of Mobile users. Mobile malwares can perform several operations which lead to cybersecurity threats such as, stealing financial or personal information, installing malicious applications, sending premium SMS, creating backdoors, keylogging and crypto-ransomware attacks. Knowing the fact that there are many illegitimate Applications available on the App stores, most of the mobile users remain careless about the security of their Mobile devices and become the potential victim of these threats. Previous studies have shown that not every antivirus is capable of detecting all the threats; due to the fact that Mobile malwares use advance techniques to avoid detection. A Network-based IDS at the operator side will bring an extra layer of security to the subscribers and can detect many advanced threats by analyzing their traffic patterns. Machine Learning(ML) will provide the ability to these systems to detect unknown threats for which signatures are not yet known. This research is focused on the evaluation of Machine Learning classifiers in Network-based Intrusion detection systems for Mobile Networks. In this study, different techniques of Network-based intrusion detection with their advantages, disadvantages and state of the art in Hybrid solutions are discussed. Finally, a ML based NIDS is proposed which will work as a subsystem, to Network-based IDS deployed by Mobile Operators, that can help in detecting unknown threats and reducing false positives. In this research, several ML classifiers were implemented and evaluated. This study is focused on Android-based malwares, as Android is the most popular OS among users, hence most targeted by cyber criminals. Supervised ML algorithms based classifiers were built using the dataset which contained the labeled instances of relevant features. These features were extracted from the traffic generated by samples of several malware families and benign applications. These classifiers were able to detect malicious traffic patterns with the TPR upto 99.6% during Cross-validation test. Also, several experiments were conducted to detect unknown malware traffic and to detect false positives. These classifiers were able to detect unknown threats with the Accuracy of 97.5%. These classifiers could be integrated with current NIDS', which use signatures, statistical or knowledge-based techniques to detect malicious traffic. Technique to integrate the output from ML classifier with traditional NIDS is discussed and proposed for future work.

The secret life of software applications

One of the most undervalued problems by smartphone users is the security of data on their mobile devices. Today smartphones and tablets are used to send messages and photos and especially to stay connected with social networks, forums and other platforms. These devices contain a lot of private information like passwords, phone numbers, private photos, emails, etc. and an attacker may choose to steal or destroy this information. The main topic of this thesis is the security of the applications present on the most popular stores (App Store for iOS and Play Store for Android) and of their mechanisms for the management of security. The analysis is focused on how the architecture of the two systems protects users from threats and highlights the real presence of malware and spyware in their respective application stores. The work described in subsequent chapters explains the study of the behavior of 50 Android applications and 50 iOS applications performed using network analysis software. Furthermore, this thesis presents some statistics about malware and spyware present on the respective stores and the permissions they require. At the end the reader will be able to understand how to recognize malicious applications and which of the two systems is more suitable for him. This is how this thesis is structured. The first chapter introduces the security mechanisms of the Android and iOS platform architectures and the security mechanisms of their respective application stores. The Second chapter explains the work done, what, why and how we have chosen the tools needed to complete our analysis. The third chapter discusses about the execution of tests, the protocol followed and the approach to assess the “level of danger” of each application that has been checked. The fourth chapter explains the results of the tests and introduces some statistics on the presence of malicious applications on Play Store and App Store. The fifth chapter is devoted to the study of the users, what they think about and how they might avoid malicious applications. The sixth chapter seeks to establish, following our methodology, what application store is safer. In the end, the seventh chapter concludes the thesis.

Mining mobile apps reviews to support release planning

The mobile apps market is a tremendous success, with millions of apps downloaded and used every day by users spread all around the world. For apps’ developers, having their apps published on one of the major app stores (e.g. Google Play market) is just the beginning of the apps lifecycle. Indeed, in order to successfully compete with the other apps in the market, an app has to be updated frequently by adding new attractive features and by fixing existing bugs. Clearly, any developer interested in increasing the success of her app should try to implement features desired by the app’s users and to fix bugs affecting the user experience of many of them. A precious source of information to decide how to collect users’ opinions and wishes is represented by the reviews left by users on the store from which they downloaded the app. However, to exploit such information the app’s developer should manually read each user review and verify if it contains useful information (e.g. suggestions for new features). This is something not doable if the app receives hundreds of reviews per day, as happens for the very popular apps on the market. In this work, our aim is to provide support to mobile apps developers by proposing a novel approach exploiting data mining, natural language processing, machine learning, and clustering techniques in order to classify the user reviews on the basis of the information they contain (e.g. useless, suggestion for new features, bugs reporting). Such an approach has been empirically evaluated and made available in a web-­‐based tool publicly available to all apps’ developers. The achieved results showed that the developed tool: (i) is able to correctly categorise user reviews on the basis of their content (e.g. isolating those reporting bugs) with 78% of accuracy, (ii) produces clusters of reviews (e.g. groups together reviews indicating exactly the same bug to be fixed) that are meaningful from a developer’s point-­‐of-­‐view, and (iii) is considered useful by a software company working in the mobile apps’ development market.

Emerging perspectives on the design, use, and evaluation of mobile and handheld devices

Human-computer interaction is a growing field of study in which researchers and professionals aim to understand and evaluate the impact of new technologies on human behavior. With the integration of smart phones, tablets, and other portable devices into everyday life, there is a greater need to understand the influence of such technology on the human experience. Emerging Perspectives on the Design, Use, and Evaluation of Mobile and Handheld Devices is an authoritative reference source consisting of the latest scholarly research and theories from international experts and professionals on the topic of human-computer interaction with mobile devices. Featuring a comprehensive collection of chapters on critical topics in this dynamic field, this publication is an essential reference source for researchers, educators, students, and practitioners interested in the use of mobile and handheld devices and their impact on individuals and society as a whole. This publication features timely, research-based chapters pertaining to topics in the design and evaluation of smart devices including, but not limited to, app stores, category-based interfaces, gamified mobility applications, mobile interaction, mobile learning, pervasive multimodal applications, smartphone interaction, and social media use.

Prototype and proof of concept for a display system in retail stores

Selling devices on retail stores comes with the big challenge of grabbing the customer’s attention. Nowadays people have a lot of offers at their disposal and new marketing techniques must emerge to differentiate the products. When it comes to smartphones and tablets, those devices can make the difference by themselves, if we use their computing power and capabilities to create something unique and interactive. With that in mind, three prototypes were developed during an internship: a face recognition based Customer Detection, a face tracking solution with an Avatar and interactive cross-app Guides. All three revealed to have potential to be differentiating solutions in a retail store, not only raising the chance of a customer taking notice of the device but also of interacting with them to learn more about their features. The results were meant to be only proof of concepts and therefore were not tested in the real world.

Investigating relationships between relationship quality, customer loyalty and cooperation : an empirical study of convenience stores' franchise chain systems in Taiwan

Franchising has been widely accepted as an effective way to conduct and expand businesses. However, a franchise system is not a guarantee of success in the market. A successful franchise system should rely on a close and strong franchising relationship. Franchising is an important relationship management business. Franchising arrangements normally last for a number of years, so the franchisor and franchisee in the arrangement relationship are usually motivated to cooperate with each other. In addition, highly loyal franchisees may be obtained through a successful long-term franchising relationship. Over the last few decades, there has been a tremendous wave of interest in franchising relationships. However, little research has been conducted to determine the reasons for long-term franchising relationships. As a result, this study focuses on the important elements that might lead to a successful long-term franchising relationship. This study attempts to examine empirically three essential constructs (relationship quality, cooperation and customer loyalty), which might lead to successful long-term franchising relationships between franchisees and franchisors among the convenience stores in Taiwan. Mailed questionnaires were utilised to collect the research data. A total of 500 surveys were mailed randomly to the manager/supervisor of convenience stores’ franchisees among the four main franchisors (7-ELEVEN, Family, Hi-Life and OK) in Taiwan. The final sample size is 120, yielding a response rate of 24 per cent. The results show that relationship quality positively influences the cooperative relationships between franchisors and franchisees. Relationship quality is also positively correlated with franchisees’ loyalty. Additionally, the results indicate that the cooperative relationships between franchisors and franchisees are significantly associated with franchisees’ loyalty.

Is there an App for that? : social media uses for road safety

The use of social media has increased dramatically in recent years in the areas of public health and injury prevention, with many organisations creating online and social media content. Despite the adoption of such media by modern society, research relating to the design and evaluation of social media for the promotion of health issues is very much in its infancy. A timely review of the available evidence in relation to the use of social media campaigns from both the road safety and broader public health context will be undertaken. In particular, this paper will address the questions of what social media should be developed, how it should be evaluated, as well as what should be the key measures of success and to what extent do these measures relate to practically significant outcomes, such as behaviour change. Much like more traditional media campaigns, social media may be best regarded as another approach within the array of potential approaches that a health advertising researcher or practitioner may utilise. With younger demographics becoming less likely to engage with more traditional advertising mediums relative to their preference for social media, social media‟s most important role in the road safety advertising context may be to offer the means of delivering road safety messages to high risk, younger road users.

Investigating relationships between relationship quality, customer loyalty and cooperation : an empirical study of convenience stores' franchise chain systems

Small business has been shown to contribute significantly to a nation’s economic development. Small business owners typically confront challenges, uncertainty, and risks while operating new businesses. Franchising has become a way to minimize the risks of small business management (Chiou et al., 2004); however, a franchise system is not a guarantee of business success (Lee and Karkovista, 2001). A poor franchising relationship between franchisors and franchisees can result in franchise failure, such as termination and closure, or franchisee exit (Frazer and Winzar, 2005).

Online retailing versus traditional stores in the purchasing decision making process

Due to proliferation of online stores prior expectations that retailing would move completely online were not fulfilled. Previous research about consumers’ preference of retailing channels suggested that online sales are driven by the convenience of online shopping, or as a natural extension of online searches. This paradigm has changed over the years. Changes in consumer behaviour are indicating that while consumers are searching online using various information sources to learn about products, ultimately when purchasing, consumers are shifting between online and offline retailing channels depending on various factors. Online shopping is still considered to be a convenient way to purchase goods, but the convenience is not the key factor. This qualitative research is based on 22 in-depth interviews with shoppers in Australia.

Data warehousing model for integrating fragmented electronic health records from disparate and heterogeneous clinical data stores

This research was a step forward in developing a data integration framework for Electronic Health Records. The outcome of the research is a conceptual and logical Data Warehousing model for integrating Cardiac Surgery electronic data records. This thesis investigated the main obstacles for the healthcare data integration and proposes a data warehousing model suitable for integrating fragmented data in a Cardiac Surgery Unit.

The effects of portal website attitude and e-services on branding of e-stores

Purpose –Increasingly the company websites, along with the intermediary websites such as portal sites have become an integral component of the firms brand strategy. This study emphasises the importance of website service elements within portal sites and the impact on e-retailer brand attitudes and brand identity in an ever more competitive digital market-space. Design/methodology/approach– The research employs structural equation modeling technique to capture the relationship among website attitude, e-service quality, brand attitude and brand identity. Findings–The results from the study indicate consumer attitude perceptions toward portal website and e-service elements combine to increase brand attitude and also brand identity for e-retailers. Originality/value –Although there has been a plethora of studies evaluating corporate websites and branding interactions there is limited comprehension of the impact of intermediary portal sites. Moreover, the literature is limited in validating the link between e-services with brand attitude and brand identity within a portal website context. This study develops a framework that highlights the important influence of e-services within portal websites and the impact on the firm’s brand.

Failure to repeatedly supercompensate muscle glycogen stores in highly trained men

Purpose: It is not known whether it is possible to repeatedly supercompensate muscle glycogen stores after exhaustive exercise bouts undertaken within several days. Methods: We evaluated the effect of repeated exercise-diet manipulation on muscle glycogen and triacylglycerol (IMTG) metabolism and exercise capacity in six well-trained subjects who completed an intermittent, exhaustive cycling protocol (EX) on three occasions separated by 48 h (i.e., days 1, 3, and 5) in a 5-d period. Twenty-four hours before day 1, subjects consumed a moderate (6 g·kg-1)-carbohydrate (CHO) diet, followed by 5 d of a high (12 g·kg-1·d -1)-CHO diet. Muscle biopsies were taken at rest, immediately post-EX on days 1, 3, and 5, and after 3 h of recovery on days 1 and 3. Results: Compared with day 1, resting muscle [glycogen] was elevated on day 3 but not day 5 (435 ± 57 vs 713 ± 60 vs 409 ± 40 mmol·kg -1, P < 0.001). [IMTG] was reduced by 28% (P < 0.05) after EX on day 1, but post-EX levels on days 3 and 5 were similar to rest. EX was enhanced on days 3 and 5 compared with day 1 (31.9 ± 2.5 and 35.4 ± 3.8 vs 24.1 ± 1.4 kJ·kg-1, P < 0.05). Glycogen synthase activity at rest and immediately post-EX was similar between trials. Additionally, the rates of muscle glycogen accumulation were similar during the 3-h recovery period on days 1 and 3. Conclusion: We show that well-trained men cannot repeatedly supercompensate muscle [glycogen] after glycogen-depleting exercise and 2 d of a high-CHO diet, suggesting that the mechanisms responsible for glycogen accumulation are attenuated as a consequence of successive days of glycogen-depleting exercise.

Investigating relationships between relationship quality, customer loyalty and cooperation : an empirical study of convenience stores' franchise chain systems

Franchising has become a way to minimise the risks of small business management. There has been little research into the factors that promote franchise relationship success. This study attempts to empirically examine the important elements (relationship quality, customer loyalty and cooperation), which might promote a successful long-term franchising relationship between franchisors and franchisees within the context of convenience stores in Taiwan. A model of these relationships was developed and tested. A total of 500 surveys were mailed to a random sample of convenience stores’ franchisee owners among the four main franchisors in Taiwan. The results show that relationship quality positively influences the cooperation between franchisors and franchisees and is positively correlated with franchisee loyalty. Additionally, the cooperative behaviour between franchisees and franchisors is significantly associated with franchisees’ loyalty.