2012/05/29 by Wen Qiang Wang, Wang, Wen Qiang, Dinh Tien Tuan Anh +5
Computer Science · Social Sciences · #Access Control and Trust #Cryptography and Security (cs.CR) #Distributed #FOS: Computer and information sciences #Internet Traffic Analysis and Secure E-voting #Network Security and Intrusion Detection #Parallel #Peer-to-Peer Network Technologies #and Cluster Computing (cs.DC) #cs.CR #cs.DC
paper · pdf · doi:10.48550/arxiv.1205.6349
openalex publication_date 2012/05/29 · arxiv created 2012/05/31 · arxiv updated 2012/06/01 · openalex created_date 2025/10/24 · openalex updated_date 2026/07/28
The proliferation of sensing devices create plethora of data-streams, which in turn can be harnessed to carry out sophisticated analytics to support various real-time applications and services as well as long-term planning, e.g., in the context of intelligent cities or smart homes to name a few prominent ones. A mature cloud infrastructure brings such a vision closer to reality than ever before. However, we believe that the ability for data-owners to flexibly and easily to control the granularity at which they share their data with other entities is very important - in making data owners feel comfortable to share to start with, and also to leverage on such fine-grained control to realize different business models or logics. In this paper, we explore some basic operations to flexibly control the access on a data stream and propose a framework eXACML+ that extends OASIS's XACML model to achieve the same. We develop a prototype using the commercial StreamBase engine to demonstrate a seamless combination of stream data processing with (a small but important selected set of) fine-grained access control mechanisms, and study the framework's efficacy based on experiments in cloud like environments.