贵州师范大学学报:自然科学版
貴州師範大學學報:自然科學版
귀주사범대학학보:자연과학판
Journal of Guizhou Normal University(Natural Sciences)
2011年
3期
66-74
,共9页
可信计算%远程证明%证据模型
可信計算%遠程證明%證據模型
가신계산%원정증명%증거모형
trusted computing%remote attestation%evidence model
可信远程证明是可信计算技术中非常重要的一部分,而可信证据又是可信远程证明的基础。但是,通过研究现有主要可信远程证明方法发现对于可信证据研究主要存在以下几个问题:首先,证据信息不充分,不能满足可信证明的需求;其次,证据信息组织不够合理;最后,由于可信性具有一定的主观性,与用户的预期相关,但现有方法中在收集证据时没有考虑用户的预期。针对上述问题,提出了一种可信远程证明的证据模型建立方法。该方法依据可信属性建立证据模型与用户预期模型,并利用该模型对软件不同阶段的证据信息进行收集,最后,根据模型建立形式更加规范的可信证据实例,该实例表明证据信息更加多样,符合用户的预期。
可信遠程證明是可信計算技術中非常重要的一部分,而可信證據又是可信遠程證明的基礎。但是,通過研究現有主要可信遠程證明方法髮現對于可信證據研究主要存在以下幾箇問題:首先,證據信息不充分,不能滿足可信證明的需求;其次,證據信息組織不夠閤理;最後,由于可信性具有一定的主觀性,與用戶的預期相關,但現有方法中在收集證據時沒有攷慮用戶的預期。針對上述問題,提齣瞭一種可信遠程證明的證據模型建立方法。該方法依據可信屬性建立證據模型與用戶預期模型,併利用該模型對軟件不同階段的證據信息進行收集,最後,根據模型建立形式更加規範的可信證據實例,該實例錶明證據信息更加多樣,符閤用戶的預期。
가신원정증명시가신계산기술중비상중요적일부분,이가신증거우시가신원정증명적기출。단시,통과연구현유주요가신원정증명방법발현대우가신증거연구주요존재이하궤개문제:수선,증거신식불충분,불능만족가신증명적수구;기차,증거신식조직불구합리;최후,유우가신성구유일정적주관성,여용호적예기상관,단현유방법중재수집증거시몰유고필용호적예기。침대상술문제,제출료일충가신원정증명적증거모형건립방법。해방법의거가신속성건립증거모형여용호예기모형,병이용해모형대연건불동계단적증거신식진행수집,최후,근거모형건립형식경가규범적가신증거실례,해실례표명증거신식경가다양,부합용호적예기。
Trusted remote attestation is very important part of trusted computing, and trusted evidence is the basis of trusted remote attestation. However, by researching the existing attestation methods, there are several issues about trusted evidence : First, the content of evidence is rather simplistic, and it cant satisfies the requirements of users; Second, organization of the evidence is not reasonable; Fi- nally, because of subjective of trustworthiness, and relating to expectation of users, existing attestation methods don't consider the user's expectation, cause the attestation result not to be trusted by users. In the paper, we proposed a method for building the evidence model of trusted remote attestation, and given the methods of evidence collection depend on the evidence model. We built trusted evidence model by analyzing the attributes of trustworthiness, then set up more formal instance of trusted evidence. Finally, through the practical application of evidence model, the trusted evidence is more comprehensive, and fully reflects the users expectation.