Privacy-preserving enhanced dummy-generation technique for location-based services

Location-based services (LBS) has become an intrinsic part of our everyday life. However, the flexibility and convenience provided by LBS are at the cost of user privacy since untrusted LBS server can leak private information of users. To overcome the privacy issues observed in LBS, a novel dummy-generation based privacy preservation technique is proposed in this article. The proposed dummy-generation technique is a circle-based technique which generates dummy locations in the circle area and is effective against center-of-anonymized spatial region attack, map-matching attack, and location-homogeneity attack. Additionally, an edge computing enabled framework is proposed, which can be used in the IoT environment. The edge computing enabled framework helps in handling the resource poverty issues of the service requesting devices and provides the low latency solution. The security analysis of our proposed dummy-generation technique reflects that the proposed technique is resilient to specific attacks for different adversary attack models. The results obtained through simulations suggest that our technique performs better than the pre-existing techniques.