100,829 research outputs found
The mechanics of trust: a framework for research and design
With an increasing number of technologies supporting transactions over distance and replacing traditional forms of interaction, designing for trust in mediated interactions has become a key concern for researchers in human computer interaction (HCI). While much of this research focuses on increasing users’ trust, we present a framework that shifts the perspective towards factors that support trustworthy behavior. In a second step, we analyze how the presence of these factors can be signalled. We argue that it is essential to take a systemic perspective for enabling well-placed trust and trustworthy behavior in the long term. For our analysis we draw on relevant research from sociology, economics, and psychology, as well as HCI. We identify contextual properties (motivation based on temporal, social, and institutional embeddedness) and the actor's intrinsic properties (ability, and motivation based on internalized norms and benevolence) that form the basis of trustworthy behavior. Our analysis provides a frame of reference for the design of studies on trust in technology-mediated interactions, as well as a guide for identifying trust requirements in design processes. We demonstrate the application of the framework in three scenarios: call centre interactions, B2C e-commerce, and voice-enabled on-line gaming
Community-Based Security for the Internet of Things
With more and more devices becoming connectable to the internet, the number
of services but also a lot of threats increases dramatically. Security is often
a secondary matter behind functionality and comfort, but the problem has
already been recognized. Still, with many IoT devices being deployed already,
security will come step-by-step and through updates, patches and new versions
of apps and IoT software. While these updates can be safely retrieved from app
stores, the problems kick in via jailbroken devices and with the variety of
untrusted sources arising on the internet. Since hacking is typically a
community effort? these days, security could be a community goal too. The
challenges are manifold, and one reason for weak or absent security on IoT
devices is their weak computational power. In this chapter, we discuss a
community based security mechanism in which devices mutually aid each other in
secure software management. We discuss game-theoretic methods of community
formation and light-weight cryptographic means to accomplish authentic software
deployment inside the IoT device community
Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework
Cooperation is one of the behavioral traits that define human beings, however
we are still trying to understand why humans cooperate. Behavioral experiments
have been largely conducted to shed light into the mechanisms behind
cooperation and other behavioral traits. However, most of these experiments
have been conducted in laboratories with highly controlled experimental
protocols but with varied limitations which limits the reproducibility and the
generalization of the results obtained. In an attempt to overcome these
limitations, some experimental approaches have moved human behavior
experimentation from laboratories to public spaces, where behaviors occur
naturally, and have opened the participation to the general public within the
citizen science framework. Given the open nature of these environments, it is
critical to establish the appropriate protocols to maintain the same data
quality that one can obtain in the laboratories. Here, we introduce Citizen
Social Lab, a software platform designed to be used in the wild using citizen
science practices. The platform allows researchers to collect data in a more
realistic context while maintaining the scientific rigour, and it is structured
in a modular and scalable way so it can also be easily adapted for online or
brick-and-mortar experimental laboratories. Following citizen science
guidelines, the platform is designed to motivate a more general population into
participation, but also to promote engaging and learning of the scientific
research process. We also review the main results of the experiments performed
using the platform up to now, and the set of games that each experiment
includes. Finally, we evaluate some properties of the platform, such as the
heterogeneity of the samples of the experiments and their satisfaction level,
and the parameters that demonstrate the robustness of the platform and the
quality of the data collected.Comment: 17 pages, 11 figures and 4 table
PROTECT: Proximity-based Trust-advisor using Encounters for Mobile Societies
Many interactions between network users rely on trust, which is becoming
particularly important given the security breaches in the Internet today. These
problems are further exacerbated by the dynamics in wireless mobile networks.
In this paper we address the issue of trust advisory and establishment in
mobile networks, with application to ad hoc networks, including DTNs. We
utilize encounters in mobile societies in novel ways, noticing that mobility
provides opportunities to build proximity, location and similarity based trust.
Four new trust advisor filters are introduced - including encounter frequency,
duration, behavior vectors and behavior matrices - and evaluated over an
extensive set of real-world traces collected from a major university. Two sets
of statistical analyses are performed; the first examines the underlying
encounter relationships in mobile societies, and the second evaluates DTN
routing in mobile peer-to-peer networks using trust and selfishness models. We
find that for the analyzed trace, trust filters are stable in terms of growth
with time (3 filters have close to 90% overlap of users over a period of 9
weeks) and the results produced by different filters are noticeably different.
In our analysis for trust and selfishness model, our trust filters largely undo
the effect of selfishness on the unreachability in a network. Thus improving
the connectivity in a network with selfish nodes.
We hope that our initial promising results open the door for further research
on proximity-based trust
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