Malware Detection Using Deep Learning  

作　　者：Achi Harrisson Thiziers Koné Tiémoman N’guessan Behou Gérard Traoré Tiémoko Qouddouss Kabir Achi Harrisson Thiziers;Koné Tiémoman;N’guessan Behou Gérard;Traoré Tiémoko Qouddouss Kabir(Unité de Recherche et d’Expertise Numérique (UREN), Université Virtuelle de Cô,te d’Ivoire, Abidjan, Cô,te d’Ivoire)

机构地区：[1]Unité de Recherche et d’Expertise Numérique (UREN), Université Virtuelle de Cô,te d’Ivoire, Abidjan, Cô,te d’Ivoire

出　　处：《Open Journal of Applied Sciences》2023年第12期2480-2491,共12页应用科学（英文）

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.

关 键 词：Neural Network ANNS Malicious Code Malware Analysis Artificial Intelligence 

分 类 号：H31[语言文字—英语]