Smart Campus Network Wormhole Attack Detection Based on Fluctuation Factor Regulation
Currently,association knowledge graph algorithms are commonly used for detecting wormhole attacks in smart campus networks,but there is a lack of adjustment for the fluctuation factor of attack validity period,resulting in a low detection rate and poor detection effect of wormhole attacks.Therefore,a smart campus network wormhole attack detection method based on fluctuation factor adjustment is proposed in the cloud computing environment.By analyzing the principles and ideals of network wormhole attacks,a wormhole attack model is constructed,and suspicious links in the network are identified.A state function is introduced to adjust the dynamic factor of the attack validity wave,and a wormhole attack verification mechanism is established.Based on this,the characteristic attributes of wormhole attack events are extracted in the cloud computing environment,and a standard expression for measuring worm-hole attacks is constructed to achieve network wormhole attack recognition.The application results of the example show that the proposed method can effectively detect network wormhole attacks,with a higher detection rate and better detection effect.
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