Trust evaluation optimization mechanism for cloud user behavior based on FANP

Yi ZHANG; Liqin TIAN; Zenan WU; Wenxing WU

doi:10.11959/j.issn.2096-109x.2021100

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Trust evaluation optimization mechanism for cloud user behavior based on FANP

Papers | 更新时间：2024-06-03

- Trust evaluation optimization mechanism for cloud user behavior based on FANP
- Chinese Journal of Network and Information Security Vol. 8, Issue 2, Pages: 175-182(2022)
- 作者机构：
  
  1. 华北科技学院计算机学院，北京101601
  2. 青海师范大学计算机学院，青海西宁810000
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-109x.2021100
  CLC： TP393
- Online First：2022-04，
  
  Published：15 April 2022
- 稿件说明：
移动端阅览
Yi ZHANG, Liqin TIAN, Zenan WU, et al. Trust evaluation optimization mechanism for cloud user behavior based on FANP[J]. Chinese Journal of Network and Information Security, 2022, 8(2): 175-182.
DOI：

Yi ZHANG, Liqin TIAN, Zenan WU, et al. Trust evaluation optimization mechanism for cloud user behavior based on FANP[J]. Chinese Journal of Network and Information Security, 2022, 8(2): 175-182. DOI： 10.11959/j.issn.2096-109x.2021100.

摘要

开放的云计算环境面临着安全挑战，传统的用户行为评估机制已经无法保障云端的安全性。为科学量化评估用户的行为信任，确保权重赋值科学合理，提高云平台下用户行为的安全可信度，设计出一种结合模糊网络分析法的信任评估优化机制。将模型中用户行为信任评估一个控制目标扩展为历史访问行为与当前访问环境两个控制目标模块，同时将历史访问行为模块划分为常规行为与灰色行为两个方面，将当前访问环境模块划分为信息完整性与访问安全性两个方面。在不同的控制目标下划分相对应的控制准则，从而构造不同控制目标下的网络分析模型，借助网络层次分析法软件计算各个目标模块下的极限超矩阵从而获取各个元素最终的稳定权重。选取开发平台下的真实用户行为数据来综合计算出不同模块下的信任度作为最终的行为评估结果。用户行为评估模块的扩展细化了评估粒度使评估结果的客观性更强，准确性更高。实验结果表明，与传统的用户行为信任评估模型相比，在相同恶意比率的云环境下，所提优化机制对恶意用户具有更好的识别效果，能够更早更快地识别出信任度低的云用户，从而提高了云端的安全性与合法性，同时为云环境下解决用户的安全可信问题以及进行有效的风险控制方面提供了新的研究思路。

Abstract

The open cloud computing environment is facing security challenges and the traditional user behavior evaluation mechanism cannot guarantee the security of the cloud.In order to scientifically and quantitatively evaluate the user’s behavior trust

ensure the scientific and reasonable weight assignment

improve the security and credibility of user behavior under the cloud platform

a trust evaluation optimization mechanism combined with fuzzy analytic network process (FANP) was designed.In the proposal

user behavior trust evaluation based on one control target was extended to include two control target modules which were historical access behavior and current access environment.At the same time

the historical access behavior module was divided into two aspects: conventional behavior and gray behavior

and the current access environment module was divided into two directions: information integrity and access security.The corresponding control criteria was divided to construct the analytic network process (ANP) model under different control objectives.The limit hypermatrix under each target module was calculated to obtain the final stability weight of each element with the help of network analytic hierarchy process software.And the real user behavior data under the development platform was selected to comprehensively calculate the trust degree under different modules as the final behavior evaluation result.The expansion of the user behavior evaluation module refined the evaluation granularity

which makes the evaluation results more objective and accurate.In the cloud environment with the same malicious ratio

the optimization mechanism has better recognition effect

and it can identify cloud users with low trust efficiently and effectively

so as to improve the security and legitimacy of the cloud.At the same time

it also provids new research direction for solving the problem of user security and credibility

and effective risk control in the cloud environment.

关键词

Keywords

references

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