本文選題：數(shù)據(jù)安全 + 用戶行為分析�。� 參考：《湖北民族學(xué)院》2017年碩士論文

【摘要】：保障數(shù)據(jù)安全是企業(yè)信息安全工作的首要目標(biāo),訪問(wèn)控制是實(shí)現(xiàn)這一目標(biāo)的重要措施。為了業(yè)務(wù)的連續(xù)性,企業(yè)把信息系統(tǒng)集成整合到私有云后,仍然沿用了基于角色為用戶靜態(tài)授權(quán)的訪問(wèn)控制模型,這種機(jī)制不能應(yīng)對(duì)合法用戶賬號(hào)的濫用或賬號(hào)憑證失竊帶來(lái)的威脅。本文在企業(yè)私有云環(huán)境下,使用機(jī)器學(xué)習(xí)的方法分析用戶行為,嘗試找到異常的用戶行為,計(jì)算用戶行為風(fēng)險(xiǎn),調(diào)整用戶信任等級(jí),從而調(diào)整用戶對(duì)應(yīng)的角色,使之按照不同的權(quán)限操作企業(yè)的數(shù)據(jù)和應(yīng)用子集。通過(guò)分析基于角色的訪問(wèn)控制模型在企業(yè)私有云環(huán)境下存在的不足,提出基于用戶行為分析實(shí)現(xiàn)動(dòng)態(tài)訪問(wèn)控制的必要性。分析了國(guó)內(nèi)外使用機(jī)器學(xué)習(xí)方法分析用戶行為的發(fā)展現(xiàn)狀、主要方法和應(yīng)用情況;完成了企業(yè)私有云信息系統(tǒng)集成整合環(huán)境下用戶行為的定義和形式化表示,提出了基于Hadoop和機(jī)器學(xué)習(xí)的用戶行為分析框架。實(shí)現(xiàn)了用戶行為數(shù)據(jù)的采集、存儲(chǔ)、數(shù)據(jù)預(yù)處理和使用機(jī)器學(xué)習(xí)自動(dòng)分析用戶行為的神經(jīng)網(wǎng)絡(luò)模型,給出了使用Tensor Flow訓(xùn)練神經(jīng)網(wǎng)絡(luò)和參數(shù)調(diào)優(yōu)的典型環(huán)境和過(guò)程。改進(jìn)了用戶行為風(fēng)險(xiǎn)值的計(jì)算方法,給出了用戶信任等級(jí)動(dòng)態(tài)調(diào)整的方法和流程�；谝陨涎芯�,提出了一個(gè)基于用戶行為分析的企業(yè)私有云動(dòng)態(tài)訪問(wèn)控制模型,描述了各個(gè)模塊的功能和之間的關(guān)系,給出了實(shí)現(xiàn)的途徑。本文提出的基于用戶行為分析的動(dòng)態(tài)訪問(wèn)控制模型能幫助企業(yè)在私有云環(huán)境下及時(shí)發(fā)現(xiàn)未知的安全風(fēng)險(xiǎn),及時(shí)的做出響應(yīng),并通過(guò)動(dòng)態(tài)調(diào)整用戶信任等級(jí)實(shí)現(xiàn)動(dòng)態(tài)訪問(wèn)控制,從而保障企業(yè)的數(shù)據(jù)安全。
[Abstract]:To ensure data security is the primary goal of enterprise information security work, access control is an important measure to achieve this goal. For business continuity, enterprises integrate information system integration into private cloud, and still use access control model based on role based user static authorization. This mechanism can not cope with legitimate user accounts. In the private cloud environment, this paper uses machine learning methods to analyze user behavior, tries to find abnormal user behavior, calculates user behavior risk, adjusts user's trust level, and adjusts the user's corresponding role to operate the data and application of the enterprise according to different privileges. By analyzing the shortage of role based access control model in enterprise private cloud environment, the necessity of realizing dynamic access control based on user behavior analysis is proposed. The development status, main methods and application situation of user behavior analysis using machine learning methods at home and abroad are analyzed, and the private cloud information system of enterprise is completed. The user behavior analysis framework based on Hadoop and machine learning is proposed in the integration and integration environment. The user behavior analysis framework based on Hadoop and machine learning is proposed. The neural network model of user behavior data acquisition, storage, data preprocessing and automatic analysis of user behavior by machine learning is implemented, and Tensor Flow is used to train the neural network. And the typical environment and process of parameter tuning. The calculation method of user's behavior risk value is improved and the method and process of dynamic adjustment of user trust level are given. Based on the above research, a dynamic access control model of enterprise private cloud based on user behavior analysis is proposed, and the function and relationship between each module are described, and the relationship between the functions and the relationship of each module is described. The dynamic access control model based on user behavior analysis can help enterprises discover the unknown security risk in the private cloud environment, respond in time, and dynamically adjust the user's trust level to realize the dynamic access control, and ensure the data security of the enterprise.

【學(xué)位授予單位】：湖北民族學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP309

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本文編號(hào)：1800777