A Retrievable Data Perturbation Method Used in Privacy-Preserving in Cloud Computing

With the increasing popularity of cloud computing,privacy has become one of the key problem in cloud security.When data is outsourced to the cloud,for data owners,they need to ensure the security of their privacy;for cloud service providers,they need some information of the data to provide high QoS services;and for authorized users,they need to access to the true value of data.The existing privacy-preserving methods can＇t meet all the needs of the three parties at the same time.To address this issue,we propose a retrievable data perturbation method and use it in the privacy-preserving in data outsourcing in cloud computing.Our scheme comes in four steps.Firstly,an improved random generator is proposed to generate an accurate ＂noise＂.Next,a perturbation algorithm is introduced to add noise to the original data.By doing this,the privacy information is hidden,but the mean and covariance of data which the service providers may need remain unchanged.Then,a retrieval algorithm is proposed to get the original data back from the perturbed data.Finally,we combine the retrievable perturbation with the access control process to ensure only the authorized users can retrieve the original data.The experiments show that our scheme perturbs date correctly,efficiently,and securely.     

云计算中基于生物共生机制改进粒子群优化的任务调度方案

针对传统的基于智能算法的云计算任务调度方案获取最优解用时较多的问题,受生物界共生现象的启发,提出一种基于生物共生机制(SM)改进粒子群优化(PSO)的任务调度方案。首先,将PSO中的粒子分成2个种群,各自执行寻优。然后,每执行k次PSO迭代后,将两个种群中的个体进行互利共生和寄生操作。通过互利共生操作使搜索过程穿过最佳解区域,从而增强搜索能力;通过寄生操作排除较差解并引入较优解来防止过早收敛。最终获得任务调度的最优解。仿真结果表明,提出的优化算法可快速收敛,相比其他几种较新的调度方案,提出的方案能够获得最小的任务完成时间和响应时间。     

现场总线的应用分析

根据现场总线的应用领域,即过程自动化、工厂自动化与运动控制,着重分析现场总线在过程自动化方面的应用。适用于过程自动化的现场总线有FF,Profibus,Profinet与EPA,从应用的情况来看都不理想,重点就上述总线的优缺点进行了分析。阐述了基于无线传感器网络,智能化现场仪表与计算相结合的云控制系统CCS（Cloud Control System）的发展趋势。     

支持高效撤销的属性加密方案

属性加密(Attribute-BasedEncryption,ABE)将密钥和密文与一系列属性相关联,被广泛应用于云计算的访问控制中。针对现有撤销方案效率低下的问题,提出一种更高效、细粒度的访问控制方案。方案中采用的访问结构可以表达任意涉及布尔运算符的访问策略;在加密过程中,构建一种属性用户组随机密钥分发方法,并结合ABE实现双重加密,将所有撤销操作转化成属性级别细粒度的撤销;新方案的数据始终以密文形式存在于服务器上,降低了对服务器的安全限制,可以将大部分密文重加密任务转移给云服务器执行,有效利用云服务器的计算能力,提升系统的运行效率,减少通信开销。     

Parallel Web Mining System Based on Cloud Platform

Traditional machine-learning algorithms are struggling to handle the exceedingly large amount of data being generated by the internet. In real-world applications, there is an urgent need for machine-learning algorithms to be able to handle large-scale, high-dimensional text data. Cloud computing involves the delivery of computing and storage as a service to a heterogeneous community of recipients. Recently, it has aroused much interest in industry and academia. Most previous works on cloud platforms only focus on the parallel algorithms for structured data. In this paper, we focus on the parallel implementation of web-mining algorithms and develop a parallel web-mining system that includes parallel web crawler; parallel text extract, transform and load (ETL) and modeling; and parallel text mining and application subsystems. The complete system enables variable real-world web-mining applications for mass data.     

Defense schemes for variants of distributed denial-of-service (DDoS) attacks in cloud computing: A survey

Cloud computing is a fast-growing and promising technology segment that aims to reduce maintenance and management costs by shifting high-quality computing infrastructure to the Internet. It is emerging as a dominant technology because it provides an on-demand, self-service, scalable, and pay-per-use business model. Despite its numerous benefits, it suffers from several security challenges. As a consequence of on-demand service, availability of computing resources is the crucial attribute of cloud computing among security necessities. In this work, a survey is presented on various issues related to the availability of resources in a cloud environment. Ensuring availability and security of computing/storage resources are still challenging tasks. The adversary class readily exploits the vulnerabilities in the cloud infrastructure for attack implementation. The article presents a study of various categories of distributed denial-of-service (DDoS) attacks in cloud computing and their defense mechanisms. It is believed that this is the first work which surveys all varieties of DDoS attacks in the cloud environment.     

改进自适应遗传算法在关联规则中的研究

针对传统的关联规则在大数据环境下数据挖掘过程中效率低的问题,文中融入了遗传算法,并且对传统的遗传算法进行优化以便更好地适用于关联规则的挖掘。针对传统的自适应遗传算法,对其交叉算子和变异算子进行自适应优化,在此基础上加入兴趣度用来剔除一些没有实际效果的规则。实验结果表明在关联规则提取方面,结合云计算技术和所改进的算法可以优化其挖掘效率,并克服适应性和可用性等方面的缺陷,不仅加快了算法的收敛速度,也提高了解的质量。     

2012年最新测试发展趋势及IXIA新一代测试平台

介绍了2012年最新测试发展趋势和IXIA新一代测试平台XcellonTM系列测试板卡,以及它的分类、支持的测试范围、超高的性能指标、端口密度和创新的聚合模式。