Exploring the impact of trust information visualization on mobile application usage

Trust allows people to live in a risky and uncertain situation by providing the means to decrease complexity. It is the key to decision making and engaging in usage. Visualizing trust information could thus leverage usage behavior and decisions. This article explores the impact of trust information visualization on mobile application usage with a three-stage experiment conducted in both Finland and China (1) by studying users’ opinions on the importance of mobile applications, (2) by evaluating the impact of a trust indicator on mobile application usage, and (3) by evaluating the impact of a trust/reputation indicator on mobile application usage. Although the results achieved in this study for Finland and China showed small differences on usage willingness and remarkable difference on trust information check willingness, both countries indicated that visualizing the reputation value of an application and/or the individual trust value of a user can assist in mobile application usage with different importance rates. In addition, the article discusses possible reasons for the difference in impact in Finland and China, other impact factors related to mobile application usage, and implications of our experiments with regard to a trust management system for mobile applications.     

PerContRep: a practical reputation system for pervasive content services

Social network has extended its popularity from the Internet to mobile domain. Personal mobile devices can be self-organized and communicate with each other for instant social activities at any time and in any places to achieve pervasive social networking (PSN). In such a network, various content information flows. To which extent should mobile users trust it, whilst user privacy can also be preserved? Existing work has not yet seriously considered trust and reputation management, although trust plays an important role in PSN. In this paper, we propose PerContRep, a practical reputation system for pervasive content services that can assist trustworthy content selection and consumption in a pervasive manner. We develop a hybrid trust and reputation management model to evaluate node recommendation trust and content reputation in the context of frequent change of node pseudonyms. Simulations show the advantages of PerContRep in assisting user decisions and its effectiveness with regard to unfair rating attack, collaborative unfair rating attack, on-off attack and conflict behavior attack. A prototype system achieves positive user feedback on its usability and social acceptance.     

分布式环境下行为感知的信任管理

针对分布式环境下信任管理的不确定性,在基于角色的信任管理基础上,引入行为感知的分析方法,以此作为信任评价的依据。将行为对信任域的影响量化为固定区间内的信任值,通过统计用户群的累积行为,计算出角色声望和域声望,并反馈调整信任域之间的信任委托关系。静态角色和动态行为的结合有效地增强了分布式网络的信任保障能力。     

Usability study of ME2.0

Mobile context-aware applications execute in the background of hosts mobile devices. The applications source process and aggregate hosts’ contextual and personal information. This information is disclosed to ubiquitously pervasive services that adapt their offerings to individual preferences. Unfortunately, many developers continue to ignore the user perspective in context-aware application designs as they complicate their overall task and generate exponential requirements. The additional incorporation of privacy mechanisms in context-aware applications to safeguard context and personal information disclosures also complicates users’ tasks resulting to misconfigured or completely abandoned applications. Misconfigured applications give end-users a false assurance of privacy exposing them to comprising services. We present a usability study on Mobile Electronic Personality Version 2 a privacy enhanced context-aware mobile application for personalising ubiquitous services and adapting pervasive smart-spaces. We draw conclusions on key issues related to user needs, based on user interviews, surveys, prototypes and field evaluations. Users’ needs are evaluated against five themes, learn-ability, efficiency, memorability, errors, satisfaction and privacy contention. In addition, design layout preferences, privacy manageability and consensus design comprehension are also evaluated. Clarity of priorities in context-aware mobile applications shaped by usability studies effectively increases the acceptance of levels of potential users.     

A novel application recommendation method combining social relationship and trust relationship for future internet of things

Traditional collaborative filtering methods always utilize Cosine and Pearson methods to calculate the similarity of users. When the nearest neighbor doesn’t comment the predicted item, then the nearest neighbor has no influence on results, thus affecting the accuracy of collaborative filtering recommendation. And the traditional recommendation systems always have the problems of data sparsity, cold start and so on. In this paper, we consider social relationship and trust relationship, and put forward a novel application recommendation method that combines users’ social relationship and trust relationship. Specifically, we combine social relationship and user preference towards applications to calculate similarity score, we fuse the trust relationship based on familiarity and user reputation to calculate trust score. The final prediction score is calculated by fusing similar relationship and trust relationship properly. And the proposed method can effectively improve accuracy of recommendations.

     

Reputation Formalization for an Information–Sharing Multi–Agent System

We propose that through the formalization of concepts related to trust, a more accurate model of trust can be implemented. This paper presents a new model of trust that is based on the formalization of reputation. A multidisciplinary approach is taken to understanding the nature of trust and its relation to reputation. Through this approach, a practical definition of reputation is adopted from sociological contexts and a model of reputation is designed and presented.
Reputation is defined as role fulfillment. To formalize reputation, it is necessary to formalize the expectations placed upon an agent within a particular multi–agent system (MAS). In this case, the agents are part of an information–sharing society. Five roles are defined along with the ways in which these roles are objectively fulfilled. Through the measurement of role fulfillment, a vector representing reputation can be developed. This vector embodies the magnitude of the reputation and describes the patterns of behavior associated with the direction of the vector.
Experiments are conducted to verify the sensibility of the proposed models for role fulfillment and overall reputation. The simulation results show that the roles, defined for building reputation in an information–sharing MAS environment, react to different agent and user actions in a manner consistent with the formal definitions.     

Factors affecting the smartphone users to use the mobile portal services: focusing on Korean mobile portals

This study aims to clarify whether and how the portal sites in wired Internet environments can enhance their positions as market leaders in the mobile environment.The result may explain that the user’s trust in the mobile services of portal sites (the mobile portal services) is related to the site’s quality and the site’s brand equity significantly and is a mediator to increase the user’s intention to use mobile portal services. This study also explains that the user’s experience with a smartphone can encourage portal users to expect that the mobile portal services are useful and that the experience can link brand equity in certain business environments to trust in the brand in other business environments. Site quality including the design quality of portal sites can affect the user’s trust in the mobile services of the portal sites directly and can affect the user’s intention to use the mobile portal services under certain conditions. Practically, this study suggests that portal sites should focus on designing and developing more usable sites with high-quality UI components—convenient menu navigation, a proper UI design, and usable content rather depend on their current position as the leading companies in the wired Internet environment.     

一种自约束信誉更新模型

在分析信誉计算模型的基础上,提出了一种自约束的信誉更新模型,由于节点的信誉主要反映历史信誉,信誉变化主要表现在新的评价分与以前信誉的变化上,因此通过自约束因子来表达这种变化。对该模型与Bayesian模型作了仿真分析比较。结果显示：信誉评估模型体现恶意行为的惩罚思想,当一个可信节点连续出现交易失败或不可信行为时,信誉值会指数级下降,恢复其信誉则是缓慢上升。     

Magentix2: A privacy-enhancing Agent Platform

Agent Platforms are the software that supports the development and execution of Multi-agent Systems. There are many Agent Platforms developed by the agent community, but they hardly consider privacy. This leads to agent-based applications that invade users’ privacy. Privacy can be threatened by two main information activities: information collection and information processing. Information collection can be prevented using traditional security mechanisms. Information processing can be prevented by minimizing data identifiability, i.e., the degree by which personal information can be directly attributed to a particular individual. However, minimizing data identifiability may directly affect other crucial issues in Multi-agent Systems, such as accountability, trust, and reputation. In this paper, we present the support that the Magentix2 Agent Platform provides for preserving privacy. Specifically, it provides mechanisms to avoid information collection and information processing when they are not desired. Moreover, Magentix2 provides these mechanisms without compromising accountability, trust, and reputation. We also provide in this paper an application built on top of Magentix2 that exploits its support for preserving privacy. Finally, we provide an extensive evaluation of the support that Magentix2 provides for preserving privacy based on that application. We specifically test whether or not privacy loss can be minimized by using the support that Magentix2 provides, whether or not this support introduces a bearable performance overhead, and whether or not existing trust and reputation models can be implemented on top of Magentix2.     

选择在线交易服务者的多情境信任和声誉评估系统

在以信任和声誉值选择服务者的系统中,普遍存在的问题是在评估服务者的信任和声誉值时考虑因素过少,局限于系统内,以及方法缺少灵活性,导致选择的服务者不能满足用户多样性的要求。为了解决这个问题,提出一种应用于在线交易服务者选择的多情境信任和声誉评估系统,服务者通过注册的质量属性和担保资金获得信任和声誉启动值,由系统内、外的交易经历获得信任和声誉经验值,实际信任和声誉值由两者动态线性组合,后者所占比重随交易次数的增加而动态增加,根据用户设置的服务者的情境属性与实际信任和声誉值选择服务者。通过与其他方法对比测试,结果表明此方法更容易满足用户的各种要求。此信任和声誉评估系统不仅能给新服务者与其他服务者一个公平竞争的环境,也可以减少用户选中恶意服务者的机会。     

Trust management and reputation systems in mobile participatory sensing applications: A survey

Participatory sensing is an emerging paradigm in which citizens everywhere voluntarily use their computational devices to capture and share sensed data from their surrounding environments in order to monitor and analyze some phenomenon (e.g., weather, road traffic, pollution, etc.). Interest in participatory sensing systems has risen since a large mobile sensor network can now be opportunistically constructed with much less cost and effort than it was the case a decade ago. However, relying on citizens who share their contributions raises many challenges. Participants can disrupt the system by contributing corrupted, fabricated, or erroneous data. Consequently, monitoring the participants’ behavior in order to estimate their honesty is an essential requirement. This enables to evaluate the veracity and accuracy of participants’ contributions and therefore, to build robust and reliable participatory sensing systems. Recently, several trust and reputation systems have been proposed to trace participants’ behavior in these systems. This survey presents a study and analysis of existing trust systems in participatory sensing applications. First, we study the nature of participatory sensing applications by surveying existing systems and outlining their common features. We then analyze the main vulnerabilities and attacks that can be launched in these systems. Furthermore, we discuss the concept of trust and we introduce a classification of existing trust systems. The two main classes of trust assessment methods for participatory sensing (i.e. Trusted Platform Module and reputation) are discussed. In addition, we analyze the merits as well as the limitations of each of them. We then derive a comparative study of several existing trust systems for participatory sensing. From this study, we identify many trust problems that have not been solved and many attacks have not been addressed yet in the literature. Finally, we list future research directions regarding trust management in participatory sensing systems.     

Understanding dynamics between initial trust and usage intentions of mobile banking

Mobile banking is an emerging application of mobile commerce that could become an additional revenue source to both banks and telecom service providers. It is a form of service convergence enabled by innovative technologies. Despite the alleged benefits of mobile banking, its acceptance has been short of industry expectations. One plausible explanation may be consumers' initial lack of trust in available services. The objective of our research is to reveal the mechanisms associated with the initial formation of people's trust in mobile banking and intention to use the service. For this, we attempt to understand the effect of four antecedent variables (structural assurances, relative benefits, personal propensity to trust and firm reputation) on shaping a person's initial trust in mobile banking and its usage intention. They represent four types of trust-inducing forces: institutional offering (structural assurances), cognition (perceived benefits), personality (personal propensity) and firm characteristics (firm reputation). We examine individual significance of the selected antecedents and also their comparative reliability in explaining the two exogenous variables. The technical basis of our empirical research is the innovative mobile banking solution that uses cellphones with a built-in smart chipset. The survey data are analyzed using structural equation modelling. The analysis showed that three variables (relative benefits, propensity to trust and structural assurances) had a significant effect on initial trust in mobile banking. Also, the perception of initial trust and relative benefits was vital in promoting personal intention to make use of related services. However, contrary to our expectation, the reputation as a firm characteristics variable failed to attract people to mobile banking.     

Social-aware hybrid mobile offloading

Mobile offloading is a promising technique to aid the constrained resources of a mobile device. By offloading a computational task, a device can save energy and increase the performance of the mobile applications. Unfortunately, in existing offloading systems, the opportunistic moments to offload a task are often sporadic and short-lived. We overcome this problem by proposing a social-aware hybrid offloading system (HyMobi), which increases the spectrum of offloading opportunities. As a mobile device is always co-located to at least one source of network infrastructure throughout of the day, by merging cloudlet, device-to-device and remote cloud offloading, we increase the availability of offloading support. Integrating these systems is not trivial. In order to keep such coupling, a strong social catalyst is required to foster user’s participation and collaboration. Thus, we equip our system with an incentive mechanism based on credit and reputation, which exploits users’ social aspects to create offload communities. We evaluate our system under controlled and in-the-wild scenarios. With credit, it is possible for a device to create opportunistic moments based on user’s present need. As a result, we extended the widely used opportunistic model with a long-term perspective that significantly improves the offloading process and encourages unsupervised offloading adoption in the wild.     

Context-aware recommendations through context and activity recognition in a mobile environment

The mobile Internet introduces new opportunities to gain insight in the user’s environment, behavior, and activity. This contextual information can be used as an additional information source to improve traditional recommendation algorithms. This paper describes a framework to detect the current context and activity of the user by analyzing data retrieved from different sensors available on mobile devices. The framework can easily be extended to detect custom activities and is built in a generic way to ensure easy integration with other applications. On top of this framework, a recommender system is built to provide users a personalized content offer, consisting of relevant information such as points-of-interest, train schedules, and touristic info, based on the user’s current context. An evaluation of the recommender system and the underlying context recognition framework shows that power consumption and data traffic is still within an acceptable range. Users who tested the recommender system via the mobile application confirmed the usability and liked to use it. The recommendations are assessed as effective and help them to discover new places and interesting information.     

TREET: the Trust and Reputation Experimentation and Evaluation Testbed

To date, trust and reputation systems have often been evaluated using methods of their designers’ own devising. Recently, we demonstrated that a number of noteworthy trust and reputation systems could be readily defeated, revealing limitations in their original evaluations. Efforts in the trust and reputation community to develop a testbed have yielded a successful competition platform, ART. This testbed, however, is less suited to general experimentation and evaluation of individual trust and reputation technologies. In this paper, we present TREET, an experimentation and evaluation testbed based directly on that used in our investigations into security vulnerabilities in trust and reputation systems for marketplaces. We demonstrate the advantages of TREET, towards the development of more thorough, objective evaluations of trust and reputation systems.     

User‐centric trust and reputation model for personal and trusted service selection

Improving quality of services (QoS) through applying trust and reputation management technology is increasingly popular in the literature and industry. Most existing trust and reputation systems calculate a general trust value or vector based on the gathered feedback without regard to trust's locality and subjectivity; therefore, they cannot effectively support a personal selection with consumer preferences. Our goal is to build a trust and reputation mechanism for facilitating a trustworthy and personal service selection in a service‐oriented Web, where service peers can act as a service provider and/or a service consumer. A user‐centric trust and reputation mechanism distinguishing the different trust context and content to enable a personal service selection with regard to trust preference in a service‐oriented Web is represented in detail. It is widely recognized that reputation‐based trust methods must face the challenge of malicious behaviors. To deal with the malicious feedback behaviors, we introduce a “bidirectional'' feedback mechanism based on QoS experience similarity in our trust and reputation framework. The test run demonstrates that our method can significantly increase the success rate of service transactions and is effective in resisting various malicious behaviors of service peers, when it is compared to other similar methods. © 2011 Wiley Periodicals, Inc.     

Understanding the evolution of consumer trust in mobile commerce: a longitudinal study

Consumer trust in mobile commerce (m-commerce) is dynamic. However, little research has examined how consumer trust in m-commerce evolves over time. Based on the extended valence theory, the self-perception theory, and the information systems expectation confirmation theory, this study examines a three-stage theoretical model of consumer trust evolution in mobile banking. We focus on the formation mechanisms of a consumer’s decision in the pre-usage stage, the feedback mechanisms of usage behavior in the usage stage, and the evaluation mechanisms in the post-usage stage. By analyzing longitudinal data collected from 332 individuals through two rounds of surveys, we find that pre-use trust has both direct and indirect influences on mobile banking usage behavior. Usage behavior provides significant feedbacks on cognitive or psychological factors, and customers’ evaluations have significant impacts on satisfaction. Satisfaction enhances post-use trust, which in turn affects future usage behavior. We also find that pre-use trust has a long term impact on post-use trust. Together, these results illustrate the dynamic process through which m-commerce consumer trust transforms.     

An Android runtime security policy enforcement framework

Today, smart phone’s malwares are deceptive enough to spoof itself as a legal mobile application. The front-end service of Trojans is attractive enough to deceive mobile users. Mobile users download similar malwares without knowing their illegitimate background threat. Unlike other vendors, Android is an open-source mobile operating system, and hence, it lacks a dedicated team to analyze the application code and decide its trustworthiness. We propose an augmented framework for Android that monitors the dynamic behavior of application during its execution. Our proposed architecture called Security Enhanced Android Framework (seaf) validates the behavior of an application through its permissions exercising patterns. Based on the exercised permissions’ combination, the mobile user is intimated about the dangerous behavior of an application. We have implemented the proposed framework within Android software stack and ported it to device. Our initial investigation shows that our solution is practical enough to be used in the consumer market.     

基于用户及其行为社会属性的信任测度模型

信任测度是信任机制的核心和基础,现有的信任机制面临着恶意用户操纵信誉的安全威胁。基于用户及其行为社会属性的信任测度模型对传统的信任机制进行了扩充,引入用户及其行为所映射的本质特性即社会属性来描述和分析恶意用户及其行为的特征,在信任测度过程中增加信誉评审过程来修正对信任测度的攻击,从而保证了分布式环境中的信任测度的可信性。模拟实验表明,该信任测度模型能有效地应对恶意用户对信誉的操纵攻击。     

A service recovery method based on trust evaluation in mobile social network

Mobile social network makes users create and share multimedia contents freely and conveniently. However, some nodes in mobile social network have malicious behavior, such as discarding or tampering packet. These factors will cause service interruptions in the process of providing multimedia contents for the user. When the service interruption happens, how to choose the more reliable backup device, reduce interruption number, increase the packet transmission efficiency and improve user’s experience of sharing multimedia contents is the object of this paper. We propose a service recovery method based on trust evaluation which adopts Dempster-Shafer (D-S) evidence theory. The service requester calculates the direct trust degree and the recommended trust degree of the backup devices, then uses the evidence combination rule to calculate the comprehensive trust degree. The backup device with the highest trust value will be seclected to recover the service. The simulation results show that this method effectively improves the packet delivery ratio, reduces the service execution time and provides users with more stable multimedia contents.