EE599-Lec17-BigData-Oct22-2013-Hwang-New(1)

Abe alleviates the access control problem by using a

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Unformatted text preview: I service, where the attributes are related to the data encrypted server to unlock the keys. 17 18 Coarse-grained access mechanisms are difficult to deploy because to secure large shared data blocks may discourage parallel processing. User cases include financial, health insurance, and personal records, etc. We have to monitor the activities around large data blocks. User cases include the life cycle of data blocks, access records, and accountability enforcement, in case abuses are detected. 19 20 An DHT-based trust overlay network for Developing a hierarchy of reputation systems for protecting cloud resource sites and datacenters (Lec.2 and 4) Prof. Kai Hwang, USC Reputation Systems for Social Networks and Cloud Systems 21 22 Conclusions : Bigdata and Cloud Growth demands a major overhaul of our educational programs in computer science, computer and networking engineering. Provenance metadata grows in complexity due to large provenance graphs generated in big-data applications. Big-data security and privacy are the major obstacles in using clouds, P2P and social networks, and the Internet of things, effectively. Analysis of large provenance graphs to detect metadata dependencies is computationally intensive for security/confidentiality apps. We must leverage the clouds to store and process big data, which changes rapidly in time and space. User cases include Insider trading, security assessment, audit logs for security compliance requirements, etc. Clouds, IoT and social networks are changing our world, reshaping human relations, and promoting the global economy and even political reform. 23 24...
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This note was uploaded on 02/04/2014 for the course EE 599 taught by Professor Povinelli during the Spring '08 term at USC.

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