Neural network-based intrusion detection method

Abstract

The invention discloses a neural network-based intrusion detection method, comprising the following steps: step 1), a detecting step which comprises the following steps: sniffing to capture traffic information of a connected host, determining which ports are open or closed and which programs are running, and judging whether the system has received an attack or is about to receive an attack according to the information; step 2), a data preprocessing step which comprises the following steps: giving a large number of training samples, selecting features, performing data preprocessing, and identifying anomalies; step 3), an attack classification step which comprises the following steps: using a decision tree model, a support vector machine or a neural network model to classify various attacksby using a neural network algorithm; and step 4), an alerting step which comprises the following steps: notifying the detected attack event, so that a network administrator can make decisions in timeand the damage caused by attacks is reduced.

Description

technical field [0001] The invention belongs to an intrusion detection method based on a neural network. Background technique [0002] With the development of the Internet, the Internet has greatly facilitated people's lives, and more and more individuals, corporate groups, or government agencies rely on the Internet to conduct business, some of which are information or secrets that are not willing to be disclosed. An insecure system can often cause losses to individuals, companies, or government agencies due to the means by which our enemies or competitors can obtain unauthorized and unauthorized information. Network intrusions have greatly threatened safe surfing the Internet and privacy protection. Due to the complexity of the network, the diversity of attack methods, and the purpose of the attacker, all of these aggravate the difficulty of network intrusion detection. At present, there are many ways to ensure system security in the market, such as installing firewall, ...

AI Technical Summary

Problems solved by technology

However, this kind of system needs to correctly distinguish between normal behavior and abnormal behavior. The boundary between them is relatively vague and difficult to accurately describe, so this kind of system often generates some false alarms.

Images