摘要
Malware represents a real threat to information systems, because of the damage it causes. This threat is growing today, as these programs take on more complex forms. This means they escape traditional malware detection methods. Hence the need for artificial intelligence, more specifically Deep Learning, which could detect malware more effectively. In this article, we’ve proposed a model for malware detection using artificial neural networks. Our approach used data from the characteristics of machines, particularly computers, to train our Deep Learning algorithm. This model demonstrated an accuracy of around 83% in predicting the presence of malware on a machine. Thus, the use of artificial neural networks for malware detection has shown his ability to assimilate complex, non-linear patterns from data.
Malware represents a real threat to information systems, because of the damage it causes. This threat is growing today, as these programs take on more complex forms. This means they escape traditional malware detection methods. Hence the need for artificial intelligence, more specifically Deep Learning, which could detect malware more effectively. In this article, we’ve proposed a model for malware detection using artificial neural networks. Our approach used data from the characteristics of machines, particularly computers, to train our Deep Learning algorithm. This model demonstrated an accuracy of around 83% in predicting the presence of malware on a machine. Thus, the use of artificial neural networks for malware detection has shown his ability to assimilate complex, non-linear patterns from data.
