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Handbook of Dynamic Data Driven Applications Systems pp 615–630Cite as

Privacy and Security Issues in DDDAS Systems

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Abstract

With the rapidly increasing prevalence of the DDDAS paradigm, privacy and security issues have come to the forefront. In the measurement, feedback, and control phases of dynamic data driven adaptive systems, protecting data integrity (security) and inferred sensitive information (privacy) from inadvertent release or malicious attack is crucial. The PREDICT (Privacy and secuRity Enhancing Dynamic Information Collection and moniToring) project investigates secure dynamic and adaptive techniques for distributed data collection and fusion, sampling and monitoring, and data modeling that preserve privacy and integrity. These approaches deliver provable guarantees of privacy and security while ensuring high fidelity, and complement encryption-based techniques. Application scenarios include health surveillance data release, traffic analysis, situation awareness and monitoring, and fleet tracking.

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Acknowledgements

This research is supported by the Air Force Office of Scientific Research (AFOSR) DDDAS program under grants FA9550-12-1-0240 and FA9550-17-1-006.

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Authors and Affiliations

  1. Emory University, Atlanta, GA, USA

    Li Xiong, Vaidy Sunderam, Liyue Fan, Slawomir Goryczka & Layla Pournajaf

Authors
  1. Li Xiong
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  2. Vaidy Sunderam
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  3. Liyue Fan
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  4. Slawomir Goryczka
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  5. Layla Pournajaf
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Corresponding author

Correspondence to Li Xiong .

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Editors and Affiliations

  1. Air Force Office of Scientific Research, Air Force Research Laboratory, Arlington, VA, USA

    Erik Blasch

  2. Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sai Ravela

  3. Information Directorate, Air Force Research Laboratory, Rome, NY, USA

    Alex Aved

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Xiong, L., Sunderam, V., Fan, L., Goryczka, S., Pournajaf, L. (2018). Privacy and Security Issues in DDDAS Systems. In: Blasch, E., Ravela, S., Aved, A. (eds) Handbook of Dynamic Data Driven Applications Systems. Springer, Cham. https://doi.org/10.1007/978-3-319-95504-9_27

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  • DOI: https://doi.org/10.1007/978-3-319-95504-9_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95503-2

  • Online ISBN: 978-3-319-95504-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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