Fast Search Processing Over Encrypted Relational Data Using K-Nearest Neighbour Algorithm

Data mining has been used in real time application in a number of areas such as for example financial, telecommunication, biological, and among government agencies and several application handle very sensitive data. So these data remains secure and private.Data encryption is a very strong option to secure the data in databases from unauthorized access and intruder.The previous privacy preserving classification techniques are not feasible for encrypted data of database.In this paper, our proposed method provides privacy-preserving classifier for encrypted data of relational databasesand achieves the better performance for extracting information from encrypted data of relational databases

GraphSE2^2: An Encrypted Graph Database for Privacy-Preserving Social Search

In this paper, we propose GraphSE$^2$, an encrypted graph database for online social network services to address massive data breaches. GraphSE$^2$ preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE$^2$ provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE$^2$ with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE$^2$ is practical for querying a social graph with a million of users.Comment: This is the full version of our AsiaCCS paper "GraphSE$^2$: An Encrypted Graph Database for Privacy-Preserving Social Search". It includes the security proof of the proposed scheme. If you want to cite our work, please cite the conference version of i

Secured Uploading and Retrieval of Data Using Visual Cryptography Scheme

Cloud storage provides a convenient, massive, and scalable storage at low cost, but data security is a major issue that prevents users from storing ?les on the cloud. This paper focuses on security for the documents that are uploaded and stored on the cloud. However, it poses risks to end users unless the data is encrypted for security. This study addresses these issues by proposing Visual Cryptography Scheme (VCS) for securing the files. In order to prevent issues like breaches and malware attacks on cloud, this innovative scheme helps in high level security to safeguard the files that are stored on the clou

Location Privacy And Geo Based Applications

— Using Geo-social networking like Apple's i Groups and Hot Potato, many people communicate with their neighbouring locations through their associates and their suggestions. Without sufficient location protection, however, these systems can be easily misused, in this paper, we introduce, a technique that provides location secrecy without adding complexity into query results. Our idea here is to secure user-specific, coordinate conversion to all location data shared with the server. The associates of a user share this user’s secret key so they can apply the same conversion. This allows all spatial queries to be evaluated correctly by the server, but our privacy mechanisms guarantee that servers are unable to see or infer the actual location data from the transformed data or from the data access