开放、共享、互联的特性使得能源互联网面临更多的网络入侵风险。如何高效、准确地检测出网络入侵行为对于能源互联网的安全稳定运行至关重要。现有基于机器学习的入侵检测算法存在无法有效处理高维入侵数据集以及实时性和准确率不高等问题。为了解决上述问题,文章提出一种基于稀疏随机投影和深度学习的入侵检测算法(intrusion detection algorithm based on sparse random projection and deep learning
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