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Abstract

 Malware detection is crucial to protect computer sys
tems against cyber threats. This project seeks to develop an 
efficient and accurate malware detection system to mitigate 
the risk of infections and protect data integrity. The General 
Objective is to develop a malware detection system using 
machine learning techniques (Analyze, Implement) that is 
able to identify and classify malicious files in real time (executable files, scripts, documents) to improve the security of 
computer systems, mainly focused on downloading video 
games.  For the development of this some methodolo
gies can be performed to satisfactorily fulfill some options 
such as: Requirements analysis and system design; Collec
tion and preparation of training data; Implementation of 
machine learning algorithms for file analysis; Evaluation 
and tuning of the malware detection model; Deployment of 
the system in a production environment. The focus of this 
platform is aimed at users of all levels who wish to down
load video games for free. Our goal is to provide a safe and 
reliable experience by allowing users to thoroughly analyze 
programs before downloading and installing any game.  
Public and private malware datasets and feature extrac
tion techniques will be used to train and validate malware 
detection models, an example can be given by analyzing 
the famous video game download site PiviGames. “We will 
develop a malware detection system to analyze files in real 
time during video game downloads. This system will identify 
potential threats and alert users to prevent infections. Our 
priority is to protect users’ computer security when down
loading games, offering peace of mind and confidence in the 
process.