人工智能对内部安全检测的负担

Tsung-Yu Ho, Wei-An Chen, Chiung-Ying Huang
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引用次数: 0

摘要

我们的研究团队多年来一直致力于通过监控网络流量来提取内部恶意行为。我们应用深度学习方法来识别网络中的恶意模式,但这种方法可能会导致更多的工作来检查人工智能模型生产的结果。因此,本文解决了考虑人工智能负担的场景,并提出了在未来工作中长期可靠检测的思路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Burden of Artificial Intelligence on Internal Security Detection
Our research team have devoted to extract internal malicious behavior by monitoring the network traffic for many years. We applied the deep learning approach to recognize the malicious patterns within network, but this methodology may lead to more works to examine the results from AI models production. Hence, this paper addressed the scenario to consider the burden of AI, and proposed an idea for long-term reliable detection in the future work.
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