Network security early warning method for DDoS attack identification based on artificial intelligence
An attack identification and network security technology, which is applied in the field of network security early warning based on artificial intelligence for DDoS attack identification, and can solve problems such as judging whether network devices have suffered DDoS attacks.
Active Publication Date: 2022-08-05
浙江御安信息技术有限公司
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[0004] In order to solve the problem that the existing method cannot effectively judge whether the network equipment of the enterprise has suffered a DDoS attack, the present invention provides a network security early warning method for DDoS attack identification based on artificial intelligence
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[0027] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be introduced below with reference to the accompanying drawings in the embodiments of the present invention.
[0028] like figure 1 As shown, a network security early warning method for DDoS attack identification based on artificial intelligence in this embodiment includes the following steps:
[0029] (1) Obtain the browser fingerprints and departments corresponding to each host of the target enterprise, and construct the host behavior code corresponding to each host according to the browser fingerprints corresponding to each host and the department; obtain the communication message information corresponding to each host, Construct the message feature code corresponding to each host according to the communication message information corresponding to each host;
[0030] Step (1) of...
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The invention relates to a network security early warning method for DDoS attack identification based on artificial intelligence, and belongs to the field of digital information transmission. The method comprises the following steps: constructing a host behavior code and a message feature code corresponding to each host in a target enterprise, and calculating a local variation domain of each period corresponding to each host; calculating the standard deviation of the tracking index corresponding to each observation time period in the use process of each host according to the local variation domain of each period corresponding to each host; calculating a network behavior abnormal index corresponding to each section of analysis time according to the standard deviation of the tracking index corresponding to each section of observation time; and judging whether the situation that the network behavior abnormal index is increased for more than two times continuously occurs in the use process of the host, if so, judging that the host initiates the DDoS attack, and giving an early warning to a manager. According to the method and the device, more effective judgment and early warning on whether the host initiates the DDoS attack are realized.
Description
technical field [0001] The invention relates to the field of digital information transmission, in particular to a network security early warning method for DDoS attack identification based on artificial intelligence. Background technique [0002] Distributed Denial of Service (DDoS) attack has always been a key research object in the field of network security. It seriously threatens the development of network security in daily work and has a huge impact on the network environment. DDoS attack refers to the use of client / server technology to combine multiple computers as an attack platform to launch DDoS attacks on one or more targets, thereby multiplying the power of denial of service attacks. [0003] When a network device is under DDoS attack, the most obvious phenomenon is that the network device receives a large number of unknown packets and data streams. For an enterprise, the network exit of a company usually corresponds to a single IP. If an abnormal host appears in ...
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IPC IPC(8): H04L9/40
CPCH04L63/1425H04L63/1458
Inventor 吴艳刘彦伸虞雁群郭银锋陈基展单易
Owner 浙江御安信息技术有限公司