在当前的数字时代，随着网络攻击日益复杂和频繁，网络安全成为了保障信息安全的重中之重。尤其是在网络入侵检测领域，传统的基于规则的检测方法已经难以应对日新月异的攻击技术。因此，利用深度学习技术进行网络入侵检测成为了研究的新趋势。本项目旨在开发一种基于卷积神经网络（CNN）和Transformer的网络入侵检测系统（IntrusionDetectNet），旨在提高检测速度和准确性，降低误报率，为网络安全领域提供新的解决方案。
☆36Apr 7, 2024Updated last year
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