A machine learning-based optical fiber eavesdropping monitoring method and related equipment
A machine learning and optical fiber technology, applied in instruments, computer components, computing, etc., can solve communication safety hazards, information leakage and other issues, and achieve the effect of improving security and enhancing anti-interception capabilities
Active Publication Date: 2021-05-04
北京光锁科技有限公司 +1
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Therefore, optical fiber eavesdropping can easily lead to information leakage and cause major security risks to communication security.
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[0035] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.
[0036] It should be noted that all expressions using "first" and "second" in the embodiments of the present invention are to distinguish two entities with the same name but different parameters or parameters that are not the same, see "first" and "second" It is only for the convenience of expression, and should not be construed as a limitation on the embodiments of the present invention, which will not be described one by one in the subsequent embodiments.
[0037] Existing monitoring methods for optical fiber eavesdropping are mainly based on the internal structural changes caused by micro-level optical power leakage and fiber damage caused by eavesdropping. Among them, there are long-wavelength signal detection methods ...
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The invention discloses a machine learning-based optical fiber wiretapping monitoring method and related equipment. The method includes: collecting historical signal information of an optical fiber communication channel, the historical signal information including wiretapping situation information and channel performance information; using a support vector machine algorithm to train according to the historical signal information, and obtaining a trained support vector machine algorithm Model; collect the signal information of the current period of the optical fiber communication channel, judge whether the signal information of the current period is eavesdropped according to the support vector machine algorithm model; if so, report to the police; if not, continue to collect the signal information of the next period signal information. The machine learning-based optical fiber eavesdropping monitoring method and related equipment of the present invention apply artificial intelligence algorithms such as machine learning to realize intelligent monitoring and identification of illegal eavesdropping.
Description
technical field [0001] The invention relates to the field of artificial intelligence, in particular to a machine learning-based optical fiber wiretapping monitoring method and related equipment. Background technique [0002] The pace of informatization development in today's world is accelerating, and communication is playing an increasingly significant role. As an important part of the communication network, the safe operation of communication optical cable lines is very critical. At this stage, my country's optical cables are usually buried in the wild, which poses a security risk for information to be eavesdropped. Existing optical cable equipment cannot resist line or node eavesdropping attacks, and important military information is always at risk of being hijacked by "wired" and "serialized" information. Therefore, it is necessary for us to pay enough attention to the protection of communication optical cable lines. While promoting its rapid development, we should for...
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IPC IPC(8): H04B10/079H04L29/06G06K9/62
CPCH04B10/0795H04L63/30G06F18/214G06F18/2411
Inventor 李亚杰张杰宋浩鲲赵永利张会彬刘明哲刘守东
Owner 北京光锁科技有限公司