创建入侵检测系统输入的算法或 API
你好，我想使用神经网络开发入侵检测系统。 我知道有 41 个输入。 （我从我用来训练神经网络的数据集中知道这一点）。
我需要帮助如何捕获实时连接中的这 41 个输入。请有人帮助我或至少引导我走向正确的方向。
谢谢您提前的回答...
Hello I want to develope Intrusion detection system using neural network.
I know there are 41 inputs. ( I know this from the Dataset which I used to train the neural network) .
I need help how to capture this 41 inputs in live connection. Please somebody help me or atleast guide me in the correct direction.
Thank you for your answers in advance...
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您想要做的是特征提取或减少输入数据。
作为输入数据，我可以想象来自防火墙的日志、捕获的数据包……
作为功能，您可以拥有诸如每个时间单位失败的登录尝试、连接数……
但如果您想让系统与当你给它提供训练时，你需要在你处理的数据中具有与你训练它相同的特征分布（或者至少非常相似）。
因此，为了让事情变得简单明了：如果您想使用您引用的训练数据，您需要了解他们在收集训练数据时到底使用了哪些数据，以及到底如何收集这些数据。对其进行预处理。
What you are trying to do is feature extraction or reduction on your input data.
As input data I could imagine logs from a firewall, captured packets, ...
And as features you could have things like failed login attempts per time unit, number of connections, ...
But if you want to have your system work with the training you feed it, you need to have the same distribution of the features in the data you process, as you have trained it on (or at least very similar).
So to make matters short and simple : if you want to use the training data you cite, you need to get to know exactly which data they worked on gathering the training data, and exactly how they preprocessed it.
我已经回答了您的其他问题（http://stackoverflow.com/questions/7587657/building-intrusion-detection-system-but-from-where-to-begin）
更彻底。但我在这里重复一遍。
阅读这篇文章，了解有关它 (KDD99) 是如何构建的更多信息
文章 (Lee2000framework) Lee, W. &斯托尔福，SJ
用于构建入侵检测系统特征和模型的框架
ACM 翻译。信息。系统。安全，ACM，2000，3，227-261
I have answered your other question (http://stackoverflow.com/questions/7587657/building-intrusion-detection-system-but-from-where-to-begin)
more thoroughly. But I repeat here.
Read this article to learn more about how it (KDD99) is constructed
Article (Lee2000framework) Lee, W. & Stolfo, S. J.
A framework for constructing features and models for intrusion detection systems
ACM Trans. Inf. Syst. Secur., ACM, 2000, 3, 227-261