Improving Privacy and Security of User Data in Location Based Services

Abstract

Location Based Services (LBS) expose user data to malicious attacks. Approaches, evolved, so far, for preserving privacy and security, suffer from one or more anomalies, and hence the problem of securing LBS data is far from being resolved. In particular, accuracy of results vs. privacy degree, privacy vs. performance, and trust between users are open problems. In this article, we present a novel approach by integration of peer-to-peer (P2P) with the caching technique and dummies from real queries. Our approach increases efficiency, leads to improved performance, and provides solutions to many problems that have existed in the past. In addition, we offer an improved way of managing cache. Simulation demonstrates superiority of our approach over earlier ones dealing with both the ratio of privacy and that of performance.

Information technologies of 21st century and their impact on the society

“…5. Some applications of Fog computing can be found in [14][15][16]. More results on Fog computing are also available in [17][18][19].…”

“…Some applications of IoT in the field of crowd management are discussed in [14]. Some applications in of IoT in the context of privacy and security are discussed in [15,16]. Some of the key devices and associated technologies to IoT include RFID Tags [25], Internet, computers, cameras, RFID, Mobile Devices, coloured lights, RFIDs, Sensors, Sensor networks, Drones, Cloud, Fog and Dew.…”

IT applications in healthcare management: a survey

“…Jinnah was suffering from tuberculosis which was slowly but surely killing him. In [28,36,37], privacy issues of data are discussed.…”

Double Cache Approach with Wireless Technology for Preserving User Privacy

“…In pursuit of a resolution of trust issue, some researchers have proposed an idea of exchanging some information about previously visited area among peers to create a robust cloak area, which paved the way to consider storing some information on the client side [32]. The method in [23] used cache in TTP to store answers of some queries of users for the purpose of using them in future. It increased the privacy and performance level but resulted in decreasing the number of connections to server.…”

“…Existing approaches are designed to defend privacy from an outer attacker, server provider, and all other types of attacks [21] by protecting one or more components. The methods or approaches for privacy of data in LBS, as in [22], may be grouped into eight classes, namely, Each one of them has one or more kind of limitations and consolidated open problems [21][22][23][24][25], which are described below.…”