Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Dynamic self-adapting wireless sensor network invasion detection intelligence algorithm

A network intrusion detection, wireless sensor technology, applied in network topology, wireless communication, transmission system and other directions, can solve problems such as difficulty in adapting to different network structures, limiting the application scope of detection modes, etc.

Active Publication Date: 2017-04-26
CHONGQING UNIV OF POSTS & TELECOMM
View PDF5 Cites 19 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

The characteristics of the network structure provide convenience for the detection mode on the one hand, but limit the application range of the detection mode on the other hand
[0005] In summary, the current intrusion detection algorithm needs to solve two problems: 1. The current intrusion detection algorithm can usually only detect one kind of attack behavior
2. Current intrusion detection algorithms usually rely on the network structure, making it difficult to adapt to different network structures

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Dynamic self-adapting wireless sensor network invasion detection intelligence algorithm
  • Dynamic self-adapting wireless sensor network invasion detection intelligence algorithm
  • Dynamic self-adapting wireless sensor network invasion detection intelligence algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0063] The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0064] figure 1 is the structure diagram of the wireless sensor network of the present invention, the network node sends its status information (feature vector) to the base station every other time gap Δt, and the base station divides the received feature vector set into training data and test data at time point m, time The set of feature vectors in [0,n] is normal data.

[0065] figure 2 Be the algorithm flowchart of the present invention, as shown in the figure, mainly comprise the following steps:

[0066] Preprocessing: The min-max normalization method is used to normalize the network features.

[0067] Training: The training data is clustered into multiple clusters by the mean shift algorithm, and merged into two clusters according to the relative distance between the cluster centers. Mark these two clusters as normal or abnormal ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention relates to a dynamic self-adapting wireless sensor network invasion detection intelligence algorithm and belongs to the wireless sensor network information safety technology field. The algorithm comprises the following steps of using a min-max standardization method to carry out normalization on a network characteristic; through a mean value drift algorithm, clustering training data into a plurality of clusters, and merging into two clusters according to a relative distance among cluster centers; taking normal data as a template and marking the two clusters as normal clusters or abnormal clusters; distributing weights for each characteristic vector of the training data according to a distance between the characteristic vector and a cluster center where the characteristic vector is located; taking the marked and weighted training data as input of a weighted support vector machine so as to construct a decision function; through the decision function, determining whether the test data is normal or abnormal; and during a detection phase, adding detection data which is determined by the decision function into the training data at intervals of updating time so as to reconstruct the decision function. The algorithm and disposition are simple, cost is low, and the algorithm can adapt to different network structures, can detect attack behaviors with different forms and possesses an expansion capability.

Description

technical field [0001] The invention belongs to the technical field of wireless sensor network information security, and relates to a dynamic adaptive wireless sensor network intrusion detection intelligent algorithm. Background technique [0002] By collecting and analyzing sensor node information, the wireless sensor network intrusion detection system can distinguish whether the node has abnormal behavior, and send an alarm to the administrator. Intrusion detection technology can detect node attack behavior in real time, effectively making up for the lack of security defense technology. Therefore, intrusion detection technology is one of the key technologies to ensure the security of wireless sensor networks. [0003] Athmani et al. resist black hole attacks by controlling the packet transmission between nodes and base stations. This scheme can save node energy, but it is difficult to resist flooding attacks. Because flooding attacks increase the number of packets trans...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): H04W12/00H04W84/18H04L29/06H04W12/121
CPCH04L63/1441H04W12/00H04W84/18
Inventor 屈洪春邱泽良吕强宋冀生伍永波王平
Owner CHONGQING UNIV OF POSTS & TELECOMM
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products