Shenderovitz et al., 2024
| Publication | Publication Date | Title |
|---|---|---|
| Aslan et al. | A new malware classification framework based on deep learning algorithms | |
| Han et al. | MalInsight: A systematic profiling based malware detection framework | |
| Ni et al. | Malware identification using visualization images and deep learning | |
| Jindal et al. | Neurlux: dynamic malware analysis without feature engineering | |
| Fan et al. | Malicious sequential pattern mining for automatic malware detection | |
| Anderson et al. | Improving malware classification: bridging the static/dynamic gap | |
| Ghiasi et al. | Dynamic VSA: a framework for malware detection based on register contents | |
| Smith et al. | Mind the gap: On bridging the semantic gap between machine learning and malware analysis | |
| Shenderovitz et al. | Bon-APT: Detection, attribution, and explainability of APT malware using temporal segmentation of API calls | |
| Downing et al. | {DeepReflect}: Discovering malicious functionality through binary reconstruction | |
| LeDoux et al. | Malware and machine learning | |
| Zakeri et al. | A static heuristic approach to detecting malware targets | |
| Liras et al. | Feature analysis for data-driven APT-related malware discrimination | |
| Patil et al. | Malware analysis using machine learning and deep learning techniques | |
| Gandotra et al. | Tools & Techniques for Malware Analysis and Classification. | |
| Priya et al. | Review on malware classification and malware detection using transfer learning approach | |
| Bragen | Malware detection through opcode sequence analysis using machine learning | |
| Sharma | Windows malware detection using machine learning and TF-IDF enriched API calls information | |
| Li et al. | MDGraph: A novel malware detection method based on memory dump and graph neural network | |
| CN119603031B (en) | Network malicious attack monitoring method and system based on deep neural model | |
| Baychev et al. | Spearphishing malware: Do we really know the unknown? | |
| Bhusal et al. | Adversarial patterns: Building robust android malware classifiers | |
| Smith et al. | Mind the gap: On bridging the semantic gap between machine learning and information security | |
| Dhavlle et al. | A novel malware detection mechanism based on features extracted from converted malware binary images | |
| Rozenberg et al. | A method for detecting unknown malicious executables |