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Abstract Recently, several data aggregation schemes based on privacy homomorphism encryption have been proposed andinvestigated on wireless sensor networks. These data aggregation schemes provide better security compared with traditionalaggregation since cluster heads (aggregator) can directly aggregate the ciphertexts without decryption; consequently, transmissionoverhead is reduced. However, the base station only retrieves the aggregated result, not individual data, which causes two problems.First, the usage of aggregation functions is constrained. For example, the base station cannot retrieve the maximum value of allsensing data if the aggregated result is the summation of sensing data. Second, the base station cannot confirm data integrity andauthenticity via attaching message digests or signatures to each sensing sample. In this system, we attempt to overcome the above twodrawbacks. In our design, the base station can recover all sensing data even these data has been aggregated.
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RCDA: Recoverable Concealed Data Aggregation for Data Integrity in Wireless Sensor Networks
Abstract
Recently, several data aggregation schemes based on privacy homomorphism
encryption have been proposed and investigated on wireless sensor networks. These
data aggregation schemes provide better security compared with traditional
aggregation since cluster heads (aggregator) can directly aggregate the ciphertexts
without decryption; consequently, transmission overhead is reduced. However, the
base station only retrieves the aggregated result, not individual data, which causes two
problems. First, the usage of aggregation functions is constrained. For example, the base
station cannot retrieve the maximum value of all sensing data if the aggregated result is
the summation of sensing data. Second, the base station cannot confirm data integrity
and authenticity via attaching message digests or signatures to each sensing sample. In
this system, we attempt to overcome the above two drawbacks. In our design, the base
station can recover all sensing data even these data has been aggregated. This property
is called “recoverable.” Experiment results demonstrate that the transmission overhead
is still reduced even if our approach is recoverable on sensing data. Furthermore, the
design has been generalized and adopted on both homogeneous and heterogeneous
wireless sensor networks.
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0th Review 1st Review
Abstract Existing System Disadvantages Proposed System Advantages Objective System Requirements System Architecture
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