發(fā)布時(shí)間：2018-06-03 13:59

  本文選題：云計(jì)算 + 信任模型　； 參考：《合肥工業(yè)大學(xué)》2014年博士論文

【摘要】：云計(jì)算作為一種新興的信息服務(wù)模式以及大規(guī)模數(shù)據(jù)存儲(chǔ)和處理方式,正在為互聯(lián)網(wǎng)時(shí)代服務(wù)計(jì)算帶來巨大而深刻的變革,使得海量計(jì)算資源、存儲(chǔ)資源、軟件資源等通過互聯(lián)網(wǎng)平臺(tái)向外按需定制化提供,用戶使用各種網(wǎng)絡(luò)服務(wù)也變得更加方便而高效。然而,由于本身云計(jì)算環(huán)境具有巨大的開放性和復(fù)雜性,同時(shí)具有資源動(dòng)態(tài)變化、自治性強(qiáng)、注重安全性等特征,用戶在選擇使用層出不窮的云服務(wù)時(shí)面臨著各種安全、隱私等風(fēng)險(xiǎn),同時(shí)受到各大云計(jì)算發(fā)起者爆出的各種安全事故的影響,逐漸引發(fā)了用戶對(duì)云計(jì)算的信任危機(jī),也阻礙了云計(jì)算的進(jìn)一步普及和發(fā)展。在云計(jì)算面臨各種信任問題的背景下,本文的研究目標(biāo)是建立云計(jì)算信任管理機(jī)制,構(gòu)建能夠適應(yīng)云計(jì)算環(huán)境與特點(diǎn)的信任模型,在開放和動(dòng)態(tài)的云計(jì)算環(huán)境下對(duì)云服務(wù)信任度進(jìn)行有效的管理和評(píng)估,從而降低用戶選擇云服務(wù)的風(fēng)險(xiǎn)。本文具體的研究內(nèi)容包括： (1)提出了一種雙層雙視角的云服務(wù)信任評(píng)估模型——基于客觀信任和主觀信任的云服務(wù)信任評(píng)估模型,并且同時(shí)從局部和全局角度分別對(duì)云計(jì)算服務(wù)的信任度進(jìn)行綜合動(dòng)態(tài)評(píng)估。在分布式信任服務(wù)提供商(TSP)的信任管理框架的基礎(chǔ)上,從云服務(wù)的服務(wù)水平協(xié)議(SLA)記錄信息和用戶反饋信息兩種角度,對(duì)云服務(wù)的局部主觀信任(LST)、局部客觀信任(LOT)、全局主觀信任(GST)以及全局客觀信任(GOT)進(jìn)行評(píng)估,其中LST和LOT分別反映了從某云服務(wù)用戶的單一視角對(duì)云服務(wù)提供商的主觀信任及客觀信任度,GST和GOT則反映了從全體用戶視角對(duì)云服務(wù)提供商的主觀信任及客觀信任度。此外,對(duì)于多云環(huán)境,TSP之間需共享多云服務(wù)提供商在不同云中的信任信息,通過構(gòu)建TSP之間的信任傳播網(wǎng)絡(luò),從而能夠?qū)缭骗h(huán)境下的云服務(wù)提供商可信度進(jìn)行評(píng)估。通過仿真實(shí)驗(yàn),表明我們提出的信任管理框架和評(píng)估方法在識(shí)別可信和不可信云服務(wù)提供商上是有效且健壯的。 (2)提出了一種云計(jì)算信任評(píng)估的三層信任屬性框架,分別從軟(硬)件等基礎(chǔ)設(shè)施信任、平臺(tái)及服務(wù)提供商的管理和技術(shù)服務(wù)信任以及用戶服務(wù)交互提供信任上分析、提煉影響云服務(wù)信任度的各個(gè)信任屬性。并且在此框架的基礎(chǔ)上,提出了一種基于不同實(shí)體及不同視角差距模型的云服務(wù)可信評(píng)估方法。從具有相關(guān)專業(yè)經(jīng)驗(yàn)的專家視角(即可信第三方)和具有個(gè)性化信任需求的用戶視角考慮,分別提煉出云服務(wù)信任屬性的實(shí)際提供性能(Delivery Performance)、用戶感受性能(Perception Performance)以及重要性(Importance Performance)三者之間的差距,再基于差距模型從以上不同視角對(duì)云服務(wù)信任度進(jìn)行了綜合考量,得到云服務(wù)信任度的差距評(píng)估結(jié)果。該方法本質(zhì)上是一種新穎的多屬性決策模型,能夠用來衡量用戶與云服務(wù)提供者、可信第三方與云服務(wù)提供者以及用戶與可信第三方之間對(duì)相同云服務(wù)的信任評(píng)估差異,從而找出影響云服務(wù)可信度的關(guān)鍵且薄弱屬性,使得云服務(wù)提供商能夠更加高效的提升服務(wù)質(zhì)量,提高可信度。 (3)提出了一種新穎且有效的基于多屬性信任評(píng)估的個(gè)性化云服務(wù)選擇機(jī)制。云服務(wù)信任值的評(píng)估來自兩個(gè)重要方面：基于感知的信任和基于信譽(yù)的信任。對(duì)于云服務(wù)用戶來說，，需在使用服務(wù)之后向云服務(wù)系統(tǒng)反饋其服務(wù)交互的多屬性評(píng)估結(jié)果,并存儲(chǔ)在信任值數(shù)據(jù)庫和信譽(yù)值數(shù)據(jù)庫中,分別作為直接信任證據(jù)以供未來再次使用或提供給其他用戶作為間接信任證據(jù)。在抽取了以上多屬性的直接或間接信任證據(jù)之后,將基于感知的信任值和基于信譽(yù)的信任值聚合之后得到云服務(wù)信任值的最終結(jié)果。其中,基于信譽(yù)的信任值是在服務(wù)信譽(yù)值的基礎(chǔ)上疊加一個(gè)從信譽(yù)值到信任值的映射函數(shù)而獲取,該函數(shù)反應(yīng)出用戶對(duì)服務(wù)信譽(yù)的個(gè)性化偏好、偏見、信念等。通過這樣一種基于個(gè)性化信任評(píng)估的云服務(wù)選擇機(jī)制,本文提出的方法在云服務(wù)系統(tǒng)中能夠有效地為用戶選擇符合其個(gè)性化信任需求的云服務(wù)。 (4)提出了一種基于反饋評(píng)價(jià)過濾機(jī)制的信任感知云服務(wù)推薦方法,首先將云服務(wù)的屬性特征和用戶需求模型中的各項(xiàng)需求偏好進(jìn)行匹配,產(chǎn)生備選云服務(wù)。在信任構(gòu)建平臺(tái)所提供的信任反饋機(jī)制的基礎(chǔ)上,通過結(jié)合反饋評(píng)分一致性和用戶服務(wù)熟悉度兩方面因素,對(duì)云服務(wù)不公平信任反饋評(píng)分進(jìn)行了過濾。首先,反饋評(píng)分一致性原則是從反饋評(píng)分的內(nèi)部規(guī)律出發(fā),過濾掉偏離全體信任反饋評(píng)分平均水平較大的一部分評(píng)分；而用戶服務(wù)熟悉度則是根據(jù)反饋評(píng)價(jià)者對(duì)于云服務(wù)的使用及反饋行為等外部規(guī)律,結(jié)合用戶交互頻率、服務(wù)使用時(shí)間、反饋提交時(shí)間等參數(shù)過濾。最終,結(jié)合內(nèi)外兩方面因素綜合過濾不公平的反饋評(píng)價(jià)。
[Abstract]:As a new information service mode and a large data storage and processing mode, cloud computing is bringing huge and profound changes to the service computing in the Internet age. It makes the mass computing resources, storage resources, software resources and so on through the Internet platform to provide, and users use various network services as well. It is more convenient and efficient. However, because the cloud computing environment has huge openness and complexity, and has the characteristics of dynamic change of resources, strong autonomy and security, users face various security, privacy and other risks when choosing an endless cloud service. At the same time, they are exposed to various big cloud computing originators. In the background of cloud computing facing various trust problems, the aim of this paper is to establish cloud computing trust management mechanism, build trust model that can adapt to the environment and characteristics of cloud computing, and open and open. In the dynamic cloud computing environment, the trust of cloud services is managed and evaluated effectively, thus reducing the risk of user selection of cloud services.
(1) a double double perspective cloud service trust evaluation model, a cloud service trust evaluation model based on objective trust and subjective trust, is proposed, and the trust degree of cloud computing service is evaluated comprehensively and dynamically from both local and global perspectives. The foundation of trust management framework for distributed trust service provider (TSP) is based on the model of trust evaluation of cloud services. From two angles of service level protocol (SLA) record information and user feedback information, the local subjective trust (LST), local objective trust (LOT), global subjective trust (GST) and global objective trust (GOT) are evaluated, in which LST and LOT reflect the cloud service from a single perspective of a cloud service user. The subjective trust and objective trust of the provider, GST and GOT reflect the subjective and objective trust of the cloud service provider from the perspective of all users. In addition, for the multi cloud environment, the TSP needs to share the trust information of the multi cloud service provider in different clouds, and by building the trust communication network between the TSP, thus it can be able to cross the cloud. The credibility of the cloud service provider in the environment is evaluated. Through simulation experiments, it shows that our proposed trust management framework and evaluation methods are effective and robust in identifying trusted and untrusted cloud service providers.
(2) a three layer trust attribute framework for cloud computing trust evaluation is proposed. It provides trust analysis from soft (hard) components such as infrastructure trust, platform and service provider management, technical service trust and user service interaction, and extracts trust attributes that affect the trust degree of cloud services. A cloud service trustworthiness evaluation method based on different entity and different perspective gap model is proposed. The actual performance (Delivery Performance) of cloud service trust property (Delivery) and user perception performance (P) are extracted from the expert perspective of the relevant professional experience (that is, the letter of the letter) and the user's perspective of the personalized trust requirement. Erception Performance) and the gap between the importance (Importance Performance) three, and then based on the gap model to evaluate the cloud service trust from the above different perspectives, and get the result of the gap assessment of the cloud service trust. This method is essentially a new multi attribute decision model, which can be used to measure the user and the user. Cloud service providers, trusted third parties and cloud service providers, and trust assessment differences between users and trusted third parties to the same cloud services, thus identify the key and weak attributes that affect cloud service credibility, making the cloud service provider more efficient in improving the quality of service and improving credibility.
(3) a novel and effective personalized cloud service selection mechanism based on multi attribute trust evaluation is proposed. The evaluation of trust value of cloud services comes from two important aspects: perceived trust and reputation based trust. For cloud service users, the Xiang Yun service system needs to feed back the multiple genera of its service interaction after the service is used. The results of the assessment are stored in the trust value database and the reputation database as direct trust evidence for the future use again or provided to other users as indirect trust evidence. After extracting the direct or indirect trust evidence of the above multiple attributes, the perceived trust value and credit based trust value are aggregated. Then we get the final result of the trust value of the cloud service. Among them, the reputation based trust value is obtained on the basis of the service reputation value, which is superposed by a mapping function from the reputation value to the trust value. This function reflects the user's personalized preference, prejudice, belief and so on. The service selection mechanism proposed in this paper can effectively select cloud services that meet their personalized trust requirements in cloud service system.
(4) a trust aware cloud service recommendation method based on feedback evaluation and filtering mechanism is proposed. First, it matches the attribute features of the cloud service and the requirements preference of the user requirement model to generate alternative cloud services. On the basis of the trust feedback machine system provided by the trust construction platform, the consistency and consistency of the feedback score are combined with the feedback. In the two aspects of customer service familiarity, we filter the unfair trust feedback score of the cloud service. First, the principle of feedback score consistency is based on the internal rules of the feedback score, filtering out a part of the score that deviates from the average level of the whole trust feedback score, and the familiarity of the user service is based on the feedback evaluator. The use of cloud services and feedback behavior, such as the external rules, combined with user interaction frequency, service time, feedback time and other parameters filtering. Finally, combined with two aspects of internal and external factors to filter unfair feedback evaluation.
【學(xué)位授予單位】：合肥工業(yè)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.08

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