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\chapter{Conclusion}
\label{ch:conclusion}
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\begin{justify}
Technology is constantly evolving and people choose unconsciously to use their smartphone for daily tasks and in today's society this tool is inevitably a tool for work usage. Therefore, forensic analysis on these devices has an exceptional interest. This work explored the potential of GBoard, in a forensic perspective by identifying the usability of the most known GBoard features for this purpose.
\end{justify}

\begin{justify}
As described throughout this report, we developed an application to tackle the most interesting forensic assets of GBoard and integrated the reporing with the Autopsy software.
\end{justify}

\begin{justify}
The application allows to extract valuable clipboard content, take out expression and emotional status of the written conversations, pull out partially or an entire conversation throughout the caching mechanisms for translation or training models and bring out shortcuts of key words potentially valuable on criminal cases.
\end{justify}

\begin{justify}
During the development of this project, some difficulties were found essentially on reverse engineering techniques. Due to the lack of knowledge on this topic, some complex internal data structures were left behind such as the \path{UserHistory.dict} file. Other difficulties were found in replicating other GBoard dumps such as seen in \textcite{BibEntry2021Jun} were also impractical on our side due to insufficient awareness about the testing environment.
\end{justify}

\section{Future work}

\begin{justify}
After finishing our development and testing GBoard we discovered some tasks to tackle and some improvements to take after analysing the results, including doing some extensive tests with Google Pixel devices, applying Artificial intelligence on some processed results for better correctness and research more in the reverse engineering of some GBoard parts.
\end{justify}

\subsection{Google Pixel testing}

\begin{justify}
As described by \textcite{BibEntry2021Jun} some prior work has been done about GBoard in a forensics perspective. As an improvment, we tried to replicate the work and develop from there, but unfortunately, the behaviour we got was brutally different. We searched about Pixel phones, and their major selling point is their unique features that Google make on purpose. One of them interacts directly with GBoard and is advertised as exclusive to Google Pixel phones \parencite{BibEntry2020Sep}. Therefore, we believe that our different results has something to do with Pixel devices and it is worth to investigate GBoard with them.
\end{justify}

\begin{justify}
Furthermore, because this results conflicts with all our tested dumps such as database content missmatch, we decided to not implement this behaviour unless properly tested by knowing specifically what triggers this behaviour and find a mechanism to differentiate those dumps more easily and consistently parse it.
\end{justify}

\subsection{Artificial Intelligence usage}

\begin{justify}
From our real-world results, we found out that proccessed history can be difficult to interpret by the forensic analyst and manually recurring to other tables, such as assembled history, can be a tedious process and sometimes the foresic analyst cannot find a pattern easily.
\end{justify}

\begin{justify}
In this case, using Artificial Intelligence could potentially help find those patterns and, in the end, provide a sorted and more clear version to the forensic analyst to look for, improving the overall analysis of digital forensic cases.
\end{justify}

\subsection{Reverse engineering}

\begin{justify}
Due to lack of our knowledge in reverse engineering of complex data structures, some work were left behind. For those who have interests in this area, research in this topic could be beneficial to understand and find more ways to dump written conversations more easily using \path{UserHistory.dict} file. Other files may also contain useful information but seem to be structured in the same format of \path{UserHistory.dict} such as files like \path{Email.dict} and \path{Contacts.dict}, potentially provide useful information such as frequently used emails and contacts.
\end{justify}
