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Krzysztof kuhy Rudnicki
838184c85b
git-subtree-dir: Programming/ERSMS-project git-subtree-mainline:7861d69ae9git-subtree-split:d060e8285a
79 lines
3.6 KiB
TeX
79 lines
3.6 KiB
TeX
\documentclass{article}[11pt]
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\usepackage{graphicx}
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\usepackage{float}
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\title{ERSMS, Group F, Project Documentation}
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\author{Hubert Dwornik, Michał Łezka, Jakub Mazur \\ Michał Sar, Krzysztof Rudnicki}
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\begin{document}
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\maketitle
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\section{System Architecture}
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We have designed and implemented 4 microservices,
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all of microservices are written in Python using Flask framework
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\paragraph{AI recommendations}
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Based on a list of movies ids, calculates and returns list of ids recommended for user who likes given movies
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\paragraph{Analytics}
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Holds information about number of
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ratings, number of users,
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average movie ratings, ratings of
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given user which are later used in
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webinterface to show data for admins
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concerning website usage
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\paragraph{Notifications}
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Notifies user whenever there is a new movie recommend by AI recommender for them
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\paragraph{Backend}
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Updates database and mantains all ongoing and incoming communication between all microservices, both between microservies and from microservices to the webinterface
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\paragraph{Caching}
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We implemented two caches
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\begin{enumerate}
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\item Backend is cached inside Analytics Service \\
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Analytics service holds tata about users and movies,
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in order to not pull all the data from backend every time we update analytics
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(for example every day), we keep the cache of backend date in our analytics
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service
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\item AI recommendations are cached inside Notification Service \\
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AI recommendations can change whenever new movie appears, notification
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service keeps the cache of ai recommendation service in order to not
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pull all the data from the ai recommendation every time it wants to notify
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the users about new movies to recommend
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\end{enumerate}
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\paragraph{Database}
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We use postgresql database to contain data about users, movies and user ratings
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\begin{figure}[H]
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\caption{System architecture representation, webinterface although not part of microservices included to show relation with backend}
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\centering
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\includegraphics[width=\textwidth]{images/systemArchitecture.drawio.pdf}
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\end{figure}
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\section{Automated Infrastructure Management solution}
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We use \textbf{Dockerfiles}
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for each microservice, webinterface and database which
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later get combined in docker compose file, after each commit on
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\textbf{GitHub} main repository docker compose gets automatically run
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on \textbf{Google Cloud} platform and deployed
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\section{Federated authorization and authentication management in the project}
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We use industry standard \textbf{OAuth} protocol in our webinterface,
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user creates their account and logs in, we use user token to
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authorize their access on backend to their ratings and
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recommendations. We use \textbf{firebase} services to manage OAuth protocol.
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\section{Threat model with mitigations}
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Our single most important asset are user likes for specific movies \\
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We expect either bots or human agents trying to access those likes for a specific users or to modify user ratings to improve or decrease certain movies ratings \\
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To mitigate that we use:
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\begin{enumerate}
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\item Certificates on our frontend, which encrypt data transmitted between website and user
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\item OAuth which is used to authenticate user and lower amount of bots accessing our Infrastructure
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\item TLS encryption between our microservices so that even our inside communication is encrypted
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\item Google cloud default security policies allowing us to monitor odd and potentially harmfull behaviours
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\end{enumerate}
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\begin{figure}[H]
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\caption{Threat model}
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\centering
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\includegraphics[width=\textwidth]{images/threat_model.png}
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\end{figure}
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\end{document} |