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A Dynamic Protection Path Planning Method Based on Reinforcement Learning

A technology for protecting paths and enhancing learning, which is applied in the field of information security, can solve problems such as slow generation speed, state explosion, and incomplete attack path coverage, and achieve the effect of fast generation speed and high degree of protection

Active Publication Date: 2019-06-28
BEIJING INSTITUTE OF TECHNOLOGYGY
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0015] The purpose of the present invention is to propose a dynamic protection path planning method based on reinforcement learning to solve the problems of slow generation speed, state explosion or incomplete attack path inclusion in existing dynamic protection path planning methods

Method used

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  • A Dynamic Protection Path Planning Method Based on Reinforcement Learning
  • A Dynamic Protection Path Planning Method Based on Reinforcement Learning
  • A Dynamic Protection Path Planning Method Based on Reinforcement Learning

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Embodiment Construction

[0056] According to the above technical solutions, the present invention will be described in detail below in conjunction with the accompanying drawings and implementation examples.

[0057] Using the enhanced learning-based dynamic protection path planning method proposed by the present invention, the specific operation steps to obtain the information transmission node set are:

[0058] Step 1. Generate a distributed network attack graph. Specifically:

[0059] Step 1.1: Use 6 search agents to simultaneously search for unused privileged nodes in the network, and push them into the search stack of each search agent.

[0060] Step 1.2: Expand the privileged node.

[0061] Step 1.3: A search agent without a privileged node in the search stack requests one or more privileged nodes from other search agents in turn. If no privileged node in the currently requested agent returns to the requesting agent, the requesting agent sends a request to the next other agent. If the request...

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Abstract

The invention relates to a dynamic protection path planning method based on reinforcement learning, and belongs to the technical field of information security. The method specifically comprises the operating steps of 1, generating a distributed network attack graph; 2, finding the worst attack path; 3, generating a network model; and 4, acquiring the best protection path by reinforcement learning. Compared with existing technologies, the method provided by the invention has the following advantages: 1, the operation of collecting training data to train a network model is not needed; 2, online learning can be performed to continuously determine the best protection path corresponding to the different network sates at different times; 3, a protection degree to transmission data is high; and 4, the generation speed of the best protection path is high.

Description

technical field [0001] The invention relates to a dynamic protection path planning method based on reinforcement learning, which belongs to the technical field of information security. Background technique [0002] When researching network attack systems for system security checks, there are currently two main types of methods: one is based on numerical calculation (risk-based), and the other is based on graph-based expression (graph-based). The graph-based expression method refers to the use of graphs to express possible attack paths and system state transition relationships, and the network attack diagram is the most typical one based on graph expression methods. The purpose of this method is to find the attack path in the network and describe the system state that causes The changing behavior sequence describes the state of network security by integrating factors such as attacks, vulnerabilities, targets, hosts, and network connection relationships. After analyzing the n...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): H04L29/06H04L12/24
CPCH04L41/12H04L41/145H04L63/1416H04L63/1433
Inventor 胡昌振陈韵吕坤
Owner BEIJING INSTITUTE OF TECHNOLOGYGY
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