Information flow control for stream processing in clouds

  • Authors:

  • Xing Xie;Indrakshi Ray;Raman Adaikkalavan;Rose Gamble

  • Affiliations:

  • Colorado State University, Fort Collins, CO, USA;Colorado State University, Fort Collins, CO, USA;Indiana University South Bend, South Bend, IN, USA;The University of Tulsa, Tulsa, OK, USA

  • Venue:
  • Proceedings of the 18th ACM symposium on Access control models and technologies
  • Year:
  • 2013

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Abstract

In the near future, clouds will provide situational monitoring services using streaming data. Examples of such services include health monitoring, stock market monitoring, shopping cart monitoring, and emergency control and threat management. Offering such services require securely processing data streams generated by multiple, possibly competing and/or complementing, organizations. Processing of data streams also should not cause any overt or covert leakage of information across organizations. We propose an information flow control model adapted from the Chinese Wall policy that can be used to protect against sensitive data disclosure. We propose architectures that are suitable for securely and efficiently processing streaming information belonging to different organizations. We discuss how performance can be further improved by sharing the processing of multiple queries. We demonstrate the feasibility of our approach by implementing a prototype of our system and show the overhead incurred due to the information flow constraints.