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+\@writefile{toc}{\contentsline {section}{\numberline {1}About CertainTrust}{1}}
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OpenCCE.tex

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+\documentclass[11pt,twoside,a4paper]{article}
+
+\usepackage{listings}             % Include the listings-package
+
+\begin{document}
+\title{Integrating CertainTrust into OpenCCE}
+\author{Nikolaos Alexpoulos, CROSSING S1}
+\date{August 2016}
+
+\maketitle
+
+\section{About CertainTrust}
+CertainTrust is a robust Bayesian Computational Trust model for user and agents.
+It offers a mathematically sound implementation of a Bayesian probability model in order to assess the 
+trustworthiness of agents in multi-agent systems. The system can calculate the expected trustworthiness of 
+agents based on its prior experience and can also combine evidence provided by other sources in statistically 
+sound ways. (Finally, it also offers a user interface to visualize trust when user involvement is needed.)
+By providing CertainTrust as a task to OpenCCE we want to enable users and devices to enhance their security 
+in high-risk environments.
+
+\section{Implementation}
+We have implemented OpenCCE as a Java project. More specifically, the whole fuctionality is encompassed in a 
+single class (CertainTrust.java). 
+The remainder of our classes support a graphical user interface intended to visualize trust in a user-friendly 
+way.
+
+\section{Usage examples and rules}
+\subsection{Usage examples}
+The proposed use of our task consists of a CertainTrust object constructed to handle a single trust 
+relationship. The constructor is reached by calling one of the \textit{createfromRS} or 
+\textit{createfromTC} functions. 
+After the constructor, the main and presumably more regularly used functionalities are 
+implemented by the functions \textit{addR}, \textit{addS} and \textit{addU} that respectively add positive, 
+negative and neutral 
+evidence to the statistical model. Furthermore, there are a number of ways to combine CertainTrust objects 
+by choosing a function from the set \{\textit{OR, AND, wFusion, cFusion}\}.
+\medskip \\
+A typical example of the use of the task could be the creation of a computational trust object and then the 
+incorporation of evidence in the statistical model that leads to an extracted expectation value for 
+the trustworthiness of the given agent. A small snippet is found below:
+\medskip
+\lstset{language=java}
+\begin{lstlisting}[frame=single]
+trustObject = CertainTrust.createDefault(N, name)
+trustObject.addR(posEvidence)
+trustObject.addS(negEvidence)
+expectation = trustObject.getExpectation()
+\end{lstlisting}
+
+\subsection{Rules}
+Rules regarding the use of CertainTrust address the correctness of the model and are provided as comments to 
+each function implemented in the class. They are normally handled by exceptions, but a static analysis 
+could have some benefit.
+
+\section{Algorithms Model}
+CertainTrust in its current form does not offer any variability. The task, which could be named 
+``Initialize CertainTrust Object'' is self-contained in the Java class of the same name. Providing different 
+tasks for each operation on the trust objects and grouping them together could be an option, but 
+is not considered practical at his point.
+
+\section{Questions for initilization}
+The main user choices during the initialization of the task concern the arguments of the 
+\textit{createfromRS} and \textit{createfromTC}. More specifically, the user should be able to 
+choose the name of the object, an initial (prior) trust value as well as the number N of adequate evidence.
+
+
+\end{document}