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Recent developments in the automatic transformation of protocols into Secure Multiparty Computation (SMC) interactions, and the selection of appropriate schemes for their implementation have improved usabililty of SMC. Poor performance along with data leakage or errors caused by coding mistakes and complexity had hindered SMC usability. Previous practice involved integrating the SMC code into the...
Inspection methods and cheap self-reporting procedures have been significantly employed in the field of Human-Computer Interaction for assessing the usability of interfaces, systems and technologies. However, there is a tendency to overlook aspects related to the context and features of the users during the usability assessment process. This research introduces the concept of mental workload as an...
This study describes and evaluates a novel trust model for a range of collaborative applications. The model assumes that humans routinely choose to trust their peers by relying on few recurrent presumptions, which are domain independent and which form a recognisable trust expertise. We refer to these presumptions as trust schemes, a specialised version of Walton's argumentation schemes. Evidence is...
The first aim of this article is to provide readers informally with the basic notions of defeasible and non-monotonic reasoning, logics borrowed from artificial intelligence. It then describes argumentation theory, a paradigm for implementing defeasible reasoning in practice as well as the common multi-layer schema upon which argument-based models are usually built. The second aim is to describe the...
This paper provides further evidence on the predictive power of online community traffic with regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we train a classifier using a set of features entirely extracted from web-traffic data of financial online communities. The classifier is shown to outperform the predictive power of a baseline...
This paper investigates the predictive power of online communities traffic in regard to stock prices. Using the largest dataset to date, spanning 8 years and almost the complete set of SP500 stocks, we analyze the predictive power of raw unstructured traffic without considering any sentiment associated. Our results partially challenge the assumption that raw traffic simply trails stock prices, as...
In this paper we investigate how temporal factors (i.e. factors computed by considering only the time-distribution of interactions) can be used as an evidence of an entity’s trustworthiness. While reputation and direct experience are the two most widely used sources of trust in applications, we believe that new sources of evidence and new applications should be investigated [1]. Moreover, while these...
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