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In scientific cloud workflows, large amounts of application data need to be stored in distributed data centres. To effectively store these data, a data manager must intelligently select data centres in which these data will reside. This is, however, not the case for data which must have a fixed location. When one task needs several datasets located in(More)
—Cloud computing opens a new era in IT as it can provide various elastic and scalable IT services in a pay-as-you-go fashion, where its users can reduce the huge capital investments in their own IT infrastructure. In this philosophy, users of cloud storage services no longer physically maintain direct control over their data, which makes data security one(More)
Distributed Denial-of-Service attack (DDoS) is a major threat for cloud environment. Traditional defending approaches cannot be easily applied in cloud security due to their relatively low efficiency, large storage, to name a few. In view of this challenge, a Confidence-Based Filtering method, named CBF, is investigated for cloud computing environment, in(More)
—Big data and its applications are attracting more and more research interests in recent years. As the new generation distributed computing platform, cloud computing is believed to be the most potent platform. With the data no longer under users' direct control, data security in cloud computing is becoming one of the most obstacles of the proliferation of(More)
In big data applications, data privacy is one of the most concerned issues because processing large-scale privacy-sensitive data sets often requires computation power provided by public cloud services. Sub-tree data anonymization, achieving a good trade-off between data utility and distortion, is a widely adopted scheme to anonymize data sets for privacy(More)
SUMMARY To verify fixed-time constraints in Grid workflow systems, consistency and inconsistency conditions have been defined in conventional verification work. However, with a view of the run-time uncertainty of activity completion duration, we argue that, although the conventional consistency condition is feasible, the conventional inconsistency condition(More)
Cloud computing provides massive computation power and storage capacity which enable users to deploy computation and data-intensive applications without infrastructure investment. Along the processing of such applications, a large volume of intermediate data sets will be generated, and often stored to save the cost of recomputing them. However, preserving(More)
—A large number of cloud services require users to share private data like electronic health records for data analysis or mining, bringing privacy concerns. Anonymizing data sets via generalization to satisfy certain privacy requirements such as k-anonymity is a widely used category of privacy preserving techniques. At present, the scale of data in many(More)