@inproceedings{DBLP:conf/sacmat/ColomboF18,
title = {Access Control in the Era of Big Data: State of the Art and Research 
 Directions},
author = {Pietro Colombo and Elena Ferrari},
editor = {Elisa Bertino and Dan Lin and Jorge Lobo},
url = {https://doi.org/10.1145/3205977.3205998},
doi = {10.1145/3205977.3205998},
year  = {2018},
date = {2018-01-01},
booktitle = {Proceedings of the 23nd ACM on Symposium on Access Control Models 
 and Technologies, SACMAT 2018, Indianapolis, IN, USA, June 13-15, 
 2018},
pages = {185--192},
publisher = {ACM},
abstract = {Data security and privacy issues are magnified by the volume, the variety, and the velocity of Big Data and by the lack, up to now, of a standard data model and related data manipulation language. In this paper, we focus on one of the key data security services, that is, access control, by highlighting the differences with traditional data management systems and describing a set of requirements that any access control solution for Big Data platforms may fulfill. We then describe the state of the art and discuss open research issues.},
keywords = {Big Data; Access control; Privacy; NoSQL data management systems},
pubstate = {published},
tppubtype = {inproceedings}
}

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