Trust prediction method based on exponential smoothing method and grey model

An exponential smoothing method and gray model technology, applied in the field of communication security, can solve the problem of low prediction accuracy, achieve the effect of reducing interference and improving accuracy

Active Publication Date: 2019-08-13
QINGDAO UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The purpose of this application is to provide a trust prediction method, device, equipment and computer-readable storage medium based on exponential smoothing method and gray model, to solve the problem of low prediction accuracy of traditional trust prediction schemes

Method used

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  • Trust prediction method based on exponential smoothing method and grey model
  • Trust prediction method based on exponential smoothing method and grey model
  • Trust prediction method based on exponential smoothing method and grey model

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Experimental program
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Embodiment 1

[0043] The following introduces Embodiment 1 of a trust prediction method based on exponential smoothing method and gray model provided by this application, see figure 1 , embodiment one includes:

[0044] Step S101: Obtain the historical trust value sequence of the target vehicle in the VANET;

[0045] The above-mentioned VANET is an open wireless communication network composed of vehicles and vehicles, and vehicles and fixed access points in the traffic environment. Malicious pushes and even malicious vehicles for security attacks bring security risks to the communication process. The purpose of this embodiment is to predict the trustworthiness of the target vehicle in the future based on the historical trust value sequence of the target vehicle, so as to ensure the safety and reliability of the communication process.

[0046] This embodiment can be implemented based on the current vehicle of the VANET, or can be implemented based on the fixed access point in the VANET, wh...

Embodiment 2

[0055] see figure 2 , embodiment two specifically includes:

[0056] Step S201: Obtain historical interaction records between the current vehicle and the target vehicle in the VANET;

[0057] Step S202: Divide the historical interaction records into multiple sub-interaction records according to the preset evaluation period;

[0058] Specifically, in order to effectively predict the trust value of the target vehicle, firstly, the interaction history between the current vehicle and the target vehicle is divided into m evaluation periods.

[0059] Step S203: Determine the data packet forwarding rate of each sub-interaction record, obtain the data packet forwarding rate sequence as the historical trust value sequence of the target vehicle, and determine the transaction quantity and transaction frequency of each sub-interaction record as the influencing factor sequence.

[0060] According to the sub-interaction records between the current vehicle and the target vehicle in each e...

Embodiment approach

[0133] As a specific implementation manner, it also includes:

[0134] Optimum value determination module: used to adjust the value of the smoothing coefficient by using the golden section search method with the average absolute percentage error as the objective function until the optimal value of the smoothing coefficient is obtained.

[0135] The trust prediction device based on exponential smoothing method and gray model in this embodiment is used to realize the aforementioned trust prediction method based on exponential smoothing method and gray model. The embodiment part of the trust prediction method of the model, for example, the acquisition module 401, the smoothing processing module 402, and the prediction module 403 are respectively used to realize steps S101, S102, and S103 in the above-mentioned trust prediction method based on the exponential smoothing method and the gray model. Therefore, for the specific implementation manners thereof, reference may be made to t...

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Abstract

The invention discloses a trust prediction method based on an exponential smoothing method and a grey model. The method comprises the steps of obtaining a historical trust value sequence of a target vehicle in a vehicle-mounted ad hoc network; carrying out smoothing processing on a historical trust value sequence according to an optimal value of a smoothing coefficient in a predetermined exponential smoothing method to obtain a smooth trust value sequence, and then inputting the smooth trust value sequence into a grey model constructed based on the optimal value of the smoothing coefficient toobtain a trust prediction result. Visibly, according to the method, the historical trust value sequence is processed by utilizing an exponential smoothing method, the interference of sequence randomfluctuation on a prediction result is reduced, and in addition, parameter optimization is performed on a smoothing coefficient of the exponential smoothing method and an objective function of a grey model, so that the accuracy of the prediction result is further improved. The invention also provides a trust prediction device and equipment based on the exponential smoothing method and the grey model, and a computer readable storage medium, and the effects of the trust prediction device and equipment are corresponding to those of the method.

Description

technical field [0001] The present application relates to the field of communication security, in particular to a trust prediction method, device, equipment and computer-readable storage medium based on exponential smoothing method and gray model. Background technique [0002] Vehicle Ad-hoc Networks (VANET for short) refers to an open wireless communication network composed of mutual communication between vehicles, between vehicles and fixed access points, and between vehicles and pedestrians in the traffic environment. At present, routing security has become a security issue that cannot be ignored in VANETs. In order to effectively identify malicious vehicles and ensure reliable data transmission between vehicles, trust prediction mechanisms are usually applied to routing protocols. However, traditional trust prediction schemes The prediction accuracy is low and cannot meet the actual demand. Contents of the invention [0003] The purpose of this application is to provi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H04W12/00H04W12/12H04W4/40H04W4/46H04W24/06H04W24/08H04L12/24G06F17/10H04W84/18H04W12/122H04W12/60
CPCH04W12/009H04W12/00H04W12/12H04W4/40H04W4/46H04W24/06H04W24/08H04L41/145H04L41/147G06F17/10H04W84/18H04W12/66H04W12/122
Inventor 夏辉张三顺陈飞程相国潘振宽
Owner QINGDAO UNIV
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