The 1st International Workshop on Privacy and Security of Big Data (PSBD 2014) focuses the attention on privacy and security research issues in the context of Big Data, a vibrant and challenging research context which is playing a leading role in the Database research community. Indeed, while Big Data is gaining the attention from the research community, also driven by some relevant technological innovations (like Clouds) as well as novel paradigms (like social networks), the issues of privacy and security of Big Data represent a fundamental problem in this research context, due to the fact Big Data are typically published online for supporting knowledge management and fruition processes and, in addition to this, such data are usually handled by multiple owners, with possible secure multi-part computation issues. Some of the hot topics in the context privacy and security of Big Data include: (i) privacy and security of Big Data integration and exchange; (ii) privacy and security of Big Data in data-intensive Cloud computing; (iii) system architectures in support of privacy and security of Big Data, e.g., GPUs: (iv) privacy and security issues of Big Data querying and analysis. These topics are first-class aspects to be addressed and investigated by PSBD 2014. These proceedings contain the papers selected for presentation at the workshop. We received 12 submissions from countries in North America, Europe and Asia. After careful review, the program committee selected 5 papers for presentation at the workshop. The accepted papers were presented in 2 sessions: scalable privacy-preserving and security-control methods for Big Data processing, user-oriented and data-oriented privacy methods for Big Data processing. A panel discussed advanced aspects of privacy and security of Big Data. We hope that these proceedings will serve as a valuable reference for researchers and practitioners focusing on privacy and security of Big Data.

PSBD 2014: Overview of the 1st international workshop on privacy and security of Big Data

CUZZOCREA, Alfredo Massimiliano
2014

Abstract

The 1st International Workshop on Privacy and Security of Big Data (PSBD 2014) focuses the attention on privacy and security research issues in the context of Big Data, a vibrant and challenging research context which is playing a leading role in the Database research community. Indeed, while Big Data is gaining the attention from the research community, also driven by some relevant technological innovations (like Clouds) as well as novel paradigms (like social networks), the issues of privacy and security of Big Data represent a fundamental problem in this research context, due to the fact Big Data are typically published online for supporting knowledge management and fruition processes and, in addition to this, such data are usually handled by multiple owners, with possible secure multi-part computation issues. Some of the hot topics in the context privacy and security of Big Data include: (i) privacy and security of Big Data integration and exchange; (ii) privacy and security of Big Data in data-intensive Cloud computing; (iii) system architectures in support of privacy and security of Big Data, e.g., GPUs: (iv) privacy and security issues of Big Data querying and analysis. These topics are first-class aspects to be addressed and investigated by PSBD 2014. These proceedings contain the papers selected for presentation at the workshop. We received 12 submissions from countries in North America, Europe and Asia. After careful review, the program committee selected 5 papers for presentation at the workshop. The accepted papers were presented in 2 sessions: scalable privacy-preserving and security-control methods for Big Data processing, user-oriented and data-oriented privacy methods for Big Data processing. A panel discussed advanced aspects of privacy and security of Big Data. We hope that these proceedings will serve as a valuable reference for researchers and practitioners focusing on privacy and security of Big Data.
9781450325981
9781450325981
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11368/2896364
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