Safety perception model construction method based on immune theory

A technology of perception model and construction method, applied in the field of security perception model construction based on immune theory, which can solve the problems of slow system speed, difficulty in detecting the attack type of the Internet of Things network layer, and high model update cost

Active Publication Date: 2020-05-08
JIANGXI UNIVERSITY OF FINANCE AND ECONOMICS
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Problems solved by technology

This type of detection model has problems such as slow system construction speed and high model update cost, making it difficult to detect complex and changeable attack types on the Internet of Things network layer

Method used

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  • Safety perception model construction method based on immune theory
  • Safety perception model construction method based on immune theory
  • Safety perception model construction method based on immune theory

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Embodiment

[0042] According to the genetic principle of the immune system, the length of the gene detection fragment is set to 3 (that is, N s is 3); the length of the binary bit string is set to 9 (that is, n is 9). Due to the use of binary expression, the input can be fuzzy index data. The security monitoring of the Internet of Things network layer is mainly realized through complex immune responses and dynamic evolution. The requirements for data accuracy are reduced, and the availability of data is improved. The model parameters proposed in this paper can be dynamically set according to actual needs. The parallel computing simulation language in this article is Java, the tool is JCreator, and the Swarm toolkit is installed.

[0043] In order to characterize the evolution characteristics, occurrence probability, detection range and other characteristics of various events and the comparability of calculation experiments, the initial number of simulated antigens of various attack event...

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Abstract

The invention discloses a safety perception model construction method based on an immune theory. The method comprises the following steps: 1, determining the affinity; 2, determining the antigen number; 3, determining the number of network layer security detectors; 4, obtaining energy. According to the invention, for increasingly enlarged networks and endless attacks, the current detection methodlacks adaptivity and expansibility, so that a more automatic and intelligent method needs to be studied to construct a detection model with strong adaptivity and dynamic expansibility.

Description

technical field [0001] The invention relates to the technical field of Internet of Things security, in particular to a method for constructing a security perception model based on immune theory. Background technique [0002] Traditional immune algorithms use deterministic identification methods to calculate the matching degree of antibodies and antigens, which is difficult to guarantee the accuracy of dynamic risk identification. Most of the traditional detection systems build detection models based on known pattern matching methods, and detect known network attacks by learning and training detection models from known samples and applying them to the security detection of the Internet of Things network layer. This type of detection model has problems such as slow system construction speed and high model update cost, making it difficult to detect complex and changeable attack types on the Internet of Things network layer. Contents of the invention [0003] In order to solv...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04L29/06H04L29/08H04L12/24
CPCH04L63/20H04L67/12H04L63/1416H04L41/145
Inventor 杨波杨美芳
Owner JIANGXI UNIVERSITY OF FINANCE AND ECONOMICS
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