2,199 research outputs found

    Usability and Trust in Information Systems

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    The need for people to protect themselves and their assets is as old as humankind. People's physical safety and their possessions have always been at risk from deliberate attack or accidental damage. The advance of information technology means that many individuals, as well as corporations, have an additional range of physical (equipment) and electronic (data) assets that are at risk. Furthermore, the increased number and types of interactions in cyberspace has enabled new forms of attack on people and their possessions. Consider grooming of minors in chat-rooms, or Nigerian email cons: minors were targeted by paedophiles before the creation of chat-rooms, and Nigerian criminals sent the same letters by physical mail or fax before there was email. But the technology has decreased the cost of many types of attacks, or the degree of risk for the attackers. At the same time, cyberspace is still new to many people, which means they do not understand risks, or recognise the signs of an attack, as readily as they might in the physical world. The IT industry has developed a plethora of security mechanisms, which could be used to mitigate risks or make attacks significantly more difficult. Currently, many people are either not aware of these mechanisms, or are unable or unwilling or to use them. Security experts have taken to portraying people as "the weakest link" in their efforts to deploy effective security [e.g. Schneier, 2000]. However, recent research has revealed at least some of the problem may be that security mechanisms are hard to use, or be ineffective. The review summarises current research on the usability of security mechanisms, and discusses options for increasing their usability and effectiveness

    Machine Understanding of Human Behavior

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    A widely accepted prediction is that computing will move to the background, weaving itself into the fabric of our everyday living spaces and projecting the human user into the foreground. If this prediction is to come true, then next generation computing, which we will call human computing, should be about anticipatory user interfaces that should be human-centered, built for humans based on human models. They should transcend the traditional keyboard and mouse to include natural, human-like interactive functions including understanding and emulating certain human behaviors such as affective and social signaling. This article discusses a number of components of human behavior, how they might be integrated into computers, and how far we are from realizing the front end of human computing, that is, how far are we from enabling computers to understand human behavior

    The Usefulness of Multi-Sensor Affect Detection on User Experience: An Application of Biometric Measurement Systems on Online Purchasing

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    abstract: Traditional usability methods in Human-Computer Interaction (HCI) have been extensively used to understand the usability of products. Measurements of user experience (UX) in traditional HCI studies mostly rely on task performance and observable user interactions with the product or services, such as usability tests, contextual inquiry, and subjective self-report data, including questionnaires, interviews, and usability tests. However, these studies fail to directly reflect a user’s psychological involvement and further fail to explain the cognitive processing and the related emotional arousal. Thus, capturing how users think and feel when they are using a product remains a vital challenge of user experience evaluation studies. Conversely, recent research has revealed that sensor-based affect detection technologies, such as eye tracking, electroencephalography (EEG), galvanic skin response (GSR), and facial expression analysis, effectively capture affective states and physiological responses. These methods are efficient indicators of cognitive involvement and emotional arousal and constitute effective strategies for a comprehensive measurement of UX. The literature review shows that the impacts of sensor-based affect detection systems to the UX can be categorized in two groups: (1) confirmatory to validate the results obtained from the traditional usability methods in UX evaluations; and (2) complementary to enhance the findings or provide more precise and valid evidence. Both provided comprehensive findings to uncover the issues related to mental and physiological pathways to enhance the design of product and services. Therefore, this dissertation claims that it can be efficient to integrate sensor-based affect detection technologies to solve the current gaps or weaknesses of traditional usability methods. The dissertation revealed that the multi-sensor-based UX evaluation approach through biometrics tools and software corroborated user experience identified by traditional UX methods during an online purchasing task. The use these systems enhanced the findings and provided more precise and valid evidence to predict the consumer purchasing preferences. Thus, their impact was “complementary” on overall UX evaluation. The dissertation also provided information of the unique contributions of each tool and recommended some ways user experience researchers can combine both sensor-based and traditional UX approaches to explain consumer purchasing preferences.Dissertation/ThesisDoctoral Dissertation Human Systems Engineering 201

    Make it so! Jean-Luc Picard, Bart Simpson and the design of e-public services

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    In this paper, we report on a project applying participatory design methods to include people who have experience of social exclusion (in one form or another) in designing possible technologies for e-(local)-government services. The work was part of a project for the Office of the Deputy Prime Minister in the UK, and was concerned with ‘access tokens’ that can provide personal identification for individuals accessing public services, based on technologies such as multi-functional smartcards, flash memory sticks, mobile phone SIMs or similar devices. In particular we report on our experience using the ‘pastiche scenarios’ technique recently developed by Mark Blythe. Our findings indicate that the technique can be effective and engaging in helping people to create realistic scenarios of future technology use and highlight some possible pitfalls to consider when using this technique.</p

    Can I Borrow Your ATM? Using Virtual Reality for (Simulated) In Situ Authentication Research

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    In situ evaluations of novel authentication systems, where the system is evaluated in its intended usage context, are often infeasible due to ethical and legal constraints. Consequently, researchers evaluate their authentication systems in the lab, which questions the eco-logical validity. In this work, we explore how VR can overcome the shortcomings of authentication studies conducted in the lab and contribute towards more realistic authentication research. We built a highly realistic automated teller machine (ATM) and a VR replica to investigate through a user study (N=20) the impact of in situ evaluations on an authentication system‘s usability results. We evaluated and compared: Lab studies in the real world, lab studies in VR, in situ studies in the real world, and in situ studies in VR. Our findings highlight 1) VR‘s great potential to circumvent potential restrictions researchers experience when evaluating authentication schemes and 2) the impact of the context on an authentication system‘s usability evaluation results. In situ ATM authentications took longer (+24.71% in the real world, +14.17% in VR) than authentications in a traditional (VR) lab environment and elicited a higher sense of being part of an ATM authentication scenario compared to a real-world and VR-based evaluation in the lab. Our quantitative findings, along with participants‘ qualitative feedback, provide first evidence of increased authentication realism when using VR for in situ authentication research. We provide researchers with a novel research approach to conduct (simulated) in situ authentication re-search, discuss our findings in the light of prior works, and conclude with three key lessons to support researchers in deciding when to use VR for in situ authentication research

    BioSecure: white paper for research in biometrics beyond BioSecure

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    This report is the output of a consultation process of various major stakeholders in the biometric community to identify the future biometrical research issues, an activity which employed not only researchers but representatives from the entire biometrical community, consisting of governments, industry, citizens and academia. It is one of the main efforts of the BioSecure Network of Excellence to define the agenda for future biometrical research, including systems and applications scenarios

    Heuristic Evaluation and Usability Testing of G-MoMo Applications

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    Financial technology (FinTech) has swiftly revolutionized mobile money as one of the ways of accessing financial services in developing countries. Numerous mobile money applications were developed to access mobile money services but are hindered by severe authentication security challenges, thus, forcing the researchers to design a secure multi-factor authentication (MFA) algorithm for mobile money applications. Three prototypes of native mobile money applications (G-MoMo applications) were developed to confirm that the algorithm provides high security and is feasible. This study, therefore, aimed to evaluate the usability of the G-MoMo applications using heuristic evaluation and usability testing to identify potential usability issues and provide recommendations for improvement. Heuristic evaluation and usability testing methods were used to evaluate the G-MoMo applications. The heuristic evaluation was carried out by five experts that used the 10 principles proposed by Jakob Nielsen with a five-point severity rating scale to identify the usability problems. While the usability testing was conducted with forty participants selected using a purposive sampling method to validate the usability of the G-MoMo applications by performing tasks and filling out the post-test questionnaire. Data collected were analyzed in RStudio software. Sixty-three usability issues were identified during heuristic evaluation, where 33 were minor and 30 were major. The most violated heuristic items were “help and documentation”, and “user control and freedom”, while the least violated heuristic items were “aesthetic and minimalist design” and “visibility of system status”. The usability testing findings revealed that the G-MoMo applications’ performance proved good in learnability, effectiveness, efficiency, memorability, and errors. It also provided user satisfaction, ease of use, aesthetics, usefulness, integration, and understandability. Therefore, it was highly recommended that the developers of G-MoMo applications fix the identified usability problems to make the applications more reliable and increase overall user satisfaction.info:eu-repo/semantics/publishedVersio
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