Multi-objective evaluation and optimization on trustworthy computing
Multi-objective evaluation and optimization on trustworthy computing
复制标题
可信计算的多目标评估与优化
DOI：
10.1007/s11432-015-0856-7
复制
发表时间：
2016-09
期刊：
影响因子：
--
通讯作者：
Xue C
中科院分区：
文献类型：
--
作者：
Lin C;Xue C
TC(可信计算)很重要。从20世纪80年代TCSEC成立TCB、TDI和TNI，到2003年4月TCPA的成立和TCG的重组，学术界和工业界对TC的讨论和研究已经持续了30多年。在软件可信性和网络可信性方面的探索已经有了大量的成果和认识，并且随着新技术和新环境的出现而不断发展和演变。与传统的系统和数据安全不同，引入了更多的属性来形成可信特征，包括可靠性、可生存性、正确性等，如[1]所示。参考文献[2]给出了一个软件可信度量的层次模型，该模型将软件的可信属性区分为关键属性和非关键属性。文献[3]最近在他们的航天器软件环境中将这些属性进一步应用到子属性中。以前关于TC评估的工作主要有两种方式，组合模型和状态模型。前者侧重于故障树[4]、决策图[5]、可靠性框图[6]等文献中元件间的组合逻辑关系和概率分析。基于状态的模型重点描述了基于状态的系统连续蜕变过程
TC (trustworthy computing) is important. Since the appearance of TCB in TCSEC in the 1980s and the following TDI and TNI, to the establishment of TCPA and the reorganization of TCG in April 2003, discussion and research on TC have lasted more than 30 years both in academia and industry. There are plenty of achievements and understanding in the exploration of software and networking trustworthiness, and they have been continuously developing and evolving with the appearance of new technology and environment. Different from traditional system and data security, more attributes are imported to form the trustworthy characteristics, including reliability, survivability, correctness and so on as illustrated in [1]. Ref.[2] gives a hierarchical model for trustworthy metrics of software which distinguishes the trustworthy attributes into critical and noncritical ones. Ref.[3] applies these attributes into sub-attributes further in their spacecraft software environment recently.Previous work on TC evaluation is mainly in two ways, combination model and state model. The former focuses on combinational logic relationship and probability analysis between components in references such as Fault Tree [4], Decision Diagram [5] and Reliability Block Diagram [6]. State based model focuses on description of the system’s continuous transmutation process based
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影响因子：
4.1
作者：
Yan Wu;Yaochu Jin;Xiaoxiong Liu
通讯作者：
Yan Wu;Yaochu Jin;Xiaoxiong Liu
DOI：
10.1145/2785966
发表时间：
2015-12
期刊：
ACM Trans. Inf. Syst. Secur.
影响因子：
--
作者：
P. Alexander;Lee Pike;P. Loscocco;George Coker
通讯作者：
P. Alexander;Lee Pike;P. Loscocco;George Coker
进化动态多目标优化的群体预测策略
影响因子：
11.8
作者：
Zhou, Aimin;Jin, Yaochu;Zhang, Qingfu
通讯作者：
Zhang, Qingfu
DOI：
--
发表时间：
1998-12
期刊：
--
影响因子：
--
作者：
J. Bard
通讯作者：
J. Bard
影响因子：
2.1
作者：
M. Jiang;Z. Meng;R. Shen;Xinsheng Xu
通讯作者：
M. Jiang;Z. Meng;R. Shen;Xinsheng Xu