Holographic Global Convolutional Networks for Long-Range Prediction Tasks in Malware Detection

arXiv:2403.17978v1 Announce Type: cross
Abstract: Malware detection is an interesting and valuable domain to work in because it has significant real-world impact and unique machine-learning challenges. We investigate existing long-range techniques and benchmarks and find that they're not very suitable in this problem area. In this paper, we introduce Holographic Global Convolutional Networks (HGConv) that utilize the properties of Holographic Reduced Representations (HRR) to encode and decode features from sequence elements. Unlike other global convolutional methods, our method does not …

abstract arxiv benchmarks challenges cs.ai cs.cr cs.lg detection domain global impact machine malware malware detection networks paper prediction stat.ml tasks type work world