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Lessons Learned on Machine Learning for Computer Security
IEEE Security & Privacy ( IF 1.9 ) Pub Date : 2023-09-06 , DOI: 10.1109/msec.2023.3287207 Daniel Arp 1 , Erwin Quiring 2 , Feargus Pendlebury 3 , Alexander Warnecke 4 , Fabio Pierazzi 5 , Christian Wressnegger 6 , Lorenzo Cavallaro 7 , Konrad Rieck 8
IEEE Security & Privacy ( IF 1.9 ) Pub Date : 2023-09-06 , DOI: 10.1109/msec.2023.3287207 Daniel Arp 1 , Erwin Quiring 2 , Feargus Pendlebury 3 , Alexander Warnecke 4 , Fabio Pierazzi 5 , Christian Wressnegger 6 , Lorenzo Cavallaro 7 , Konrad Rieck 8
Affiliation
We identify 10 generic pitfalls that can affect the experimental outcome of AI driven solutions in computer security. We find that they are prevalent in the literature and provide recommendations for overcoming them in the future.
中文翻译：
计算机安全机器学习的经验教训
我们确定了 10 个可能影响计算机安全领域人工智能驱动解决方案实验结果的常见陷阱。我们发现它们在文献中很普遍，并为将来克服它们提供了建议。
更新日期：2023-09-08
中文翻译：
计算机安全机器学习的经验教训
我们确定了 10 个可能影响计算机安全领域人工智能驱动解决方案实验结果的常见陷阱。我们发现它们在文献中很普遍，并为将来克服它们提供了建议。
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