TY - GEN
T1 - Security with privacy-A research agenda
AU - Bertino, Elisa
AU - Samanthula, Bharath K.
N1 - Publisher Copyright:
© 2014 ICST.
PY - 2015/1/19
Y1 - 2015/1/19
N2 - Data is one of the most valuable assets for organization. It can facilitate users or organizations to meet their diverse goals, ranging from scientific advances to business intelligence. Due to the tremendous growth of data, the notion of big data has certainly gained momentum in recent years. Cloud computing is a key technology for storing, managing and analyzing big data. However, such large, complex, and growing data, typically collected from various data sources, such as sensors and social media, can often contain personally identifiable information (PII) and thus the organizations collecting the big data may want to protect their outsourced data from the cloud. In this paper, we survey our research towards development of efficient and effective privacy-enhancing (PE) techniques for management and analysis of big data in cloud computing.We propose our initial approaches to address two important PE applications: (i) privacy-preserving data management and (ii) privacy-preserving data analysis under the cloud environment. Additionally, we point out research issues that still need to be addressed to develop comprehensive solutions to the problem of effective and efficient privacy-preserving use of data.
AB - Data is one of the most valuable assets for organization. It can facilitate users or organizations to meet their diverse goals, ranging from scientific advances to business intelligence. Due to the tremendous growth of data, the notion of big data has certainly gained momentum in recent years. Cloud computing is a key technology for storing, managing and analyzing big data. However, such large, complex, and growing data, typically collected from various data sources, such as sensors and social media, can often contain personally identifiable information (PII) and thus the organizations collecting the big data may want to protect their outsourced data from the cloud. In this paper, we survey our research towards development of efficient and effective privacy-enhancing (PE) techniques for management and analysis of big data in cloud computing.We propose our initial approaches to address two important PE applications: (i) privacy-preserving data management and (ii) privacy-preserving data analysis under the cloud environment. Additionally, we point out research issues that still need to be addressed to develop comprehensive solutions to the problem of effective and efficient privacy-preserving use of data.
UR - http://www.scopus.com/inward/record.url?scp=84922998734&partnerID=8YFLogxK
U2 - 10.4108/icst.collaboratecom.2014.257687
DO - 10.4108/icst.collaboratecom.2014.257687
M3 - Conference contribution
AN - SCOPUS:84922998734
T3 - CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing: Networking, Applications and Worksharing
SP - 144
EP - 153
BT - CollaborateCom 2014 - Proceedings of the 10th IEEE International Conference on Collaborative Computing
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE/EAI International Conference on Collaborative Computing, CollaborateCom 2014
Y2 - 22 October 2014 through 25 October 2014
ER -