@inproceedings{10.1007/978-3-030-87839-9_4,
	title        = {DexRay: A Simple, yet Effective Deep Learning Approach to Android Malware Detection Based on Image Representation of Bytecode},
	author       = {Daoudi, Nadia and Samhi, Jordan and Kabore, Abdoul Kader and Allix, Kevin and Bissyand{\'e}, Tegawend{\'e} F. and Klein, Jacques},
	year         = 2021,
	booktitle    = {Deployable Machine Learning for Security Defense},
	publisher    = {Springer International Publishing},
	address      = {Cham},
	pages        = {81--106},
	isbn         = {978-3-030-87839-9},
	editor       = {Wang, Gang and Ciptadi, Arridhana and Ahmadzadeh, Ali},
	abstract     = {Computer vision has witnessed several advances in recent years, with unprecedented performance provided by deep representation learning research. Image formats thus appear attractive to other fields such as malware detection, where deep learning on images alleviates the need for comprehensively hand-crafted features generalising to different malware variants. We postulate that this research direction could become the next frontier in Android malware detection, and therefore requires a clear roadmap to ensure that new approaches indeed bring novel contributions. We contribute with a first building block by developing and assessing a baseline pipeline for image-based malware detection with straightforward steps.}
}