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Security and Privacy Support For Data-centric Sensor Networks. PIs: Sencun Zhu and Guohong Cao, Computer Science & Engineering, PSU. Project Description

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security and privacy support for data centric sensor networks
Security and Privacy Support For Data-centric Sensor Networks

PIs: Sencun Zhu and Guohong Cao, Computer Science & Engineering, PSU

  • Project Description
    • In a data-centric sensor network, sensing data are named based on attributes such as event type and sensing data with the same name are stored in the same location, queries for data of a particular name can be sent directly to the nodes storing these data rather than flooding the query throughout the network. However, saving data in the network also creates high security and privacy problems. For example, an attacker may find out/compromise/destroy the storage nodes for the events of his interest or trace back to the data sources.
    • Example:
    • In a wild animal habitat, the detected location of each type of animal
    • is forwarded and stored in one location. The zoologist should be able
    • to query and access all the locations, whereas a hunt is only
    • authorized to access the locations of certain animals (e.g., dears
    • and boars) for hunting, not that of elephants.
    • Attack Model:
    • local passive attack – local eavesdropping, no node compromise
    • global passive attack – global eavesdropping, no compromise
    • compromise-based active attack – with node compromises
    • No one-for-all solution, we propose one approach for each
    • attack

Approach and Impact

  • Approaches
  • Principle of least privilege to restrict the access rights of mobile users
  • Anonymization techniques to prevent traffic analysis
  • keyed hash to obfuscate location mapping
  • Research Impact
  • preventing eavesdropping and traffic analysis
  • resilient to node/user compromises
  • optimal queries
  • Technical Details
  • Based on the principal of least privilege, we design several security restriction schemes
  • which only grants the user the least privilege required to accomplish their tasks.
  • Instead of using a publicly-known mapping function, we provide private data-location mapping based on various types of cryptographic keys.
  • As private mapping may reduce the efficiency of sending user queries, we also propose query optimization techniques based on keyed bloom filter to minimize the query overhead.

Publications:

M. Shao, S. Zhu, W. Zhang, G. Cao,  pDCS: Security and Privacy Support for Data-Centric Sensor Networks, IEEE INFOCOM 2007, to appear.

H. Song, W. Zhang, S. Zhu, and G. Cao. Towards Tolerating Mobile Sink Compromises in Wireless Sensor Networks. Submitted to ACM Transaction on Sensor Networks (2nd round review).