Deep learning meets malware detection: An investigation
Document Type
Book Chapter
Publication Title
Combating Security Challenges in the Age of Big Data
Publisher
Springer
School
School of Science / ECU Security Research Institute
RAS ID
31624
Abstract
From the dawn of computer programs, malware programs were originated and still with us. With evolving of technology, malware programs are also evolving. It is considered as one of the prime issues regarding cyber world security. Damage caused by the malware programs ranges from system failure to financial loss. Traditional approach for malware classification approach are not very suitable for advance malware programs. For the continuously evolving malware ecosystem deep learning approaches are more suitable as they are faster and can predict malware more effectively. To our best of knowledge, there has not substantial research done on deep learning based malware detection on different sectors like: IoT, Bio-medical sectors and Cloud platforms. The key contribution of this chapter will be creating directions of malware detection depending on deep learning. The chapter will be beneficial for graduate level students, academicians and researchers in this application domain.
DOI
10.1007/978-3-030-35642-2_7
Access Rights
subscription content
Comments
Bostami B., Ahmed M. (2020) Deep Learning Meets Malware Detection: An Investigation. In: Fadlullah Z., Khan Pathan AS. (eds) Combating Security Challenges in the Age of Big Data. Advanced Sciences and Technologies for Security Applications. Springer, Cham. https://doi.org/10.1007/978-3-030-35642-2_7