LODPD: A LOCATION DIFFERENCE-BASED PROXIMITY DETECTION PROTOCOL FOR FOG COMPUTING
ABSTRACT
Proximity detection is one of the most commonlocation-based applications in daily life when users intent tofind their friends who get into their proximity. Studies onprotecting user privacy information during the detection processhave been widely concerned. In this paper, we first analyze atheoretical and experimental analysis of existing solutions forproximity detection, and then demonstrate that these solutionseither provide a weak privacy preserving or result in a highcommunication and computational complexity. Accordingly, a locationdifference-based proximity detection protocol is proposedbased on the Paillier cryptosystem for the purpose of dealing withthe above shortcomings. The analysis results through an extensivesimulation illustrate that our protocol outperforms traditionalprotocols in terms of communication and computation cost.
EXISTING SYSTEM:
Many solutions have been proposed for LBS to protectusers’ privacy during collecting personal data, e.g. the mobilesensing. This section reviews the general privacy preservingschemes and the private proximity detection services.There existed three kinds of privacy preserving techniquesin LBS. The first one was spatial and temporal cloaking ,in which the user’s location was sent to the SP along withlocations of other k potential requesters. The user could choosethe correct result from all the query results responded bythe SP. However, this approach was not applicable in thecase of proximity detection for the reason that it may notonly decrease the detection accuracy but be easy to hurtusers’ privacy when suffering several simple attacks.The second one was location transformation method. Theuser employed this algorithm to transform the exact locationsinto a mendacious coordinates to preserve the privacy. In, although authors adopted the Hilbert curves algorithmto transform user’s location, there were still some potentialthreats which could lead to the breakdown of the system .Thirdly, private information retrieval was also used toprevent privacy leakage. The performance of this approachwas greatly improved by the usage of the secure hardware. Nevertheless, the solution had a higher requirement onuser’s mobile phones because of a high communication costs,which was not applicable in most LBS services.
PROPOSED SYSTEM:
In this paper, we propose an efficient third-party homomorphicsecure protocol to solve the above challenges, whichis called as a location difference-based proximity detectionprotocol. In our protocol, Alice could find her friends fromany polygon vicinity region that is based on her requirement.Our major contributions are summarized as below.1) A practical symmetric client-server protocol is presentedin the LBS process, which can protect the privacy of theusers’ location from disclosing to any party.2) In order to reduce the computation and communicationcost, Alice can deduce the detection results without encryptingall her proximity edges by decision-tree theory.3) We conduct extensive experiments to evaluate the performanceof our protocol and make a comparison withthe traditional PPD protocol.
CONCLUSION
In this paper, a Location Difference-based Proximity DetectionProtocol is proposed to solve the privacy preserving issuefor the proximity detection in a fog computing system, whichexploit the Paillier encryption algorithm and the decision-treetheory. Without the collusion scenario, we define a differencethat is used to determine the relative location between a edgeand Bob’s location in the protocol for the purpose of ensuringprivacy. During the detection, the parameters are transmitteda Alice, Bob and the SP in the Paillier encryption formto keep out of the external malicious attacks. Analyses andsimulation results clearly explain that our protocol outperformsthe traditional PPD method in both communication cost andCPU cost. For future work, we will extend the vicinity regionsto the closed regions of arbitrary shapes and develop an APPbased on the protocol to do more tests in a real scenario
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