Scientific workflows are today a vital tool for computational science, enabling the definition and execution of complex applications in heterogeneous and often distributed environments. A key characteristic of scientific workflow applications is that they often require the massive processing of an enormous amount of data that, in many cases, convey personal information. To allow an efficient and transparent privacy compliance check process, in this paper, we propose a blockchain-based solution coupled with an ad-hoc index structure that makes it possible an efficient compliance check for a massive amount of data.Invited Pape
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Unauthorized access to data is one of the most significant privacy issues that hinder most industrie...
Scientific workflows are today a vital tool for computational science, enabling the definition and e...
Today, most online services acquire more and more information about users, to intercept their habits...
Machine learning provides an effective approach to execute big data analysis. As a branch of machine...
Collaborative e-Science projects commonly require data analysis to be performed on distributed data ...
e-Science is getting more distributed and collaborative and data privacy quickly becomes a major con...
The Internet of Things (IoT) pervades our lives every day and has given end users the opportunity of...
Real-world applications in healthcare and supply chain domains produce, exchange, and share data in ...
Nowadays, scientific experiments are conducted in a collaborative way. In collaborative scientific e...
Business process models can involve numerous operational activities for collecting, processing and e...
The blockchain rush and its rapid adoption in our daily life raise new questions and concerns regard...
Artificial Intelligence applications rely on large amounts of data. These Artificial Intelligence ap...
Data-driven applications are engines of economic growth and essential for progress in many domains. ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Unauthorized access to data is one of the most significant privacy issues that hinder most industrie...
Scientific workflows are today a vital tool for computational science, enabling the definition and e...
Today, most online services acquire more and more information about users, to intercept their habits...
Machine learning provides an effective approach to execute big data analysis. As a branch of machine...
Collaborative e-Science projects commonly require data analysis to be performed on distributed data ...
e-Science is getting more distributed and collaborative and data privacy quickly becomes a major con...
The Internet of Things (IoT) pervades our lives every day and has given end users the opportunity of...
Real-world applications in healthcare and supply chain domains produce, exchange, and share data in ...
Nowadays, scientific experiments are conducted in a collaborative way. In collaborative scientific e...
Business process models can involve numerous operational activities for collecting, processing and e...
The blockchain rush and its rapid adoption in our daily life raise new questions and concerns regard...
Artificial Intelligence applications rely on large amounts of data. These Artificial Intelligence ap...
Data-driven applications are engines of economic growth and essential for progress in many domains. ...
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Com...
© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for a...
Unauthorized access to data is one of the most significant privacy issues that hinder most industrie...