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 "owner": "peters111",
 "name": "quovadis-speakeasy",
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 "last_modified": "2026-09-02T12:12:25.000Z",
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 "citation": "@inproceedings{quovadis,\nauthor = {Trizna, Dmitrijs},\ntitle = {Quo Vadis: Hybrid Machine Learning Meta-Model Based on Contextual and Behavioral Malware Representations},\nyear = {2022},\nisbn = {9781450398800},\npublisher = {Association for Computing Machinery},\naddress = {New York, NY, USA},\nurl = {https://doi.org/10.1145/3560830.3563726},\ndoi = {10.1145/3560830.3563726},\nbooktitle = {Proceedings of the 15th ACM Workshop on Artificial Intelligence and Security},\npages = {127–136},\nnumpages = {10},\nkeywords = {reverse engineering, neural networks, malware, emulation, convolutions},\nlocation = {Los Angeles, CA, USA},\nseries = {AISec'22}\n}\n@ARTICLE{nebula,\n  author={Trizna, Dmitrijs and Demetrio, Luca and Biggio, Battista and Roli, Fabio},\n  journal={IEEE Transactions on Information Forensics and Security}, \n  title={Nebula: Self-Attention for Dynamic Malware Analysis}, \n  year={2024},\n  volume={19},\n  number={},\n  pages={6155-6167},\n  keywords={Malware;Feature extraction;Data models;Analytical models;Long short term memory;Task analysis;Encoding;Malware;transformers;dynamic analysis;convolutional neural networks},\n  doi={10.1109/TIFS.2024.3409083}}",
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