Effective Privacy Preserving in Networks Using Merkle Hash Trees
Abstract
The design of two-tiered sensing element networks,
wherever storage nodes function Associate in performing intermediate
tier between sensors and a sink for storing knowledge and process
queries, has been wide adopted thanks to the advantages of power and
storage saving for sensors yet because the potency of question process.
However, the importance of storage nodes conjointly makes them
enticing to attackers during this paper, we have a tendency to propose
SafeQ, a protocol that forestalls attackers from gaining info from each
sensing element collected knowledge and sink issued queries. SafeQ
conjointly permits a sink to observe compromised storage nodes after
they act. To preserve privacy, SafeQ uses a unique technique to
cypher each knowledge and queries such a storage node will properly
method encoded queries over encoded knowledge while not knowing
their values. To preserve integrity, we have a tendency to propose 2
schemes—one victimization Merkle hash trees and another employing
a new system referred to as neighborhood chains—to generate
integrity verification info so a sink will use this info to verify whether
or not the results of a question contains precisely the knowledge
things that satisfy the query to boost performance, we have a tendency
to propose Associate in Nursing optimization technique victimization
Bloom filters to scale back the communication price between sensors
and storage nodes
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