Description
Type of work: Master’s thesis kNN on Encrypted Geospatial Data Motivation The search over encrypted data is an important technique in the area of cloud computing. Fully homomorphic encryption (FHE) is able to provide full computation over encrypted data, but lacks in efficiency and is not applicable for very large data sets until now. Somewhat homomorphic encryption (SHE) on the other hand, provides the ability to do efficient partial computation on encrypted data. In combination with other cryptographic techniques like Order Preserving Encryption (hOPE) and Structured Encryption (SE) this allows us, to compute operations on encrypted graph data. In this master thesis a query operation on encrypted graph data, a so called kNN query, shall be conceived, developed, tested and evaluated. In a kNN query the k next neighbours to a point are returned on request. Testing shall be done on real world encrypted geospatial data. Topic The goal of this thesis is to develop an encrypted kNN query, based on the Paillier crpytosystem in combination with hOPE and SE. In order to conceived such an encrypted kNN query, various steps have to be completed. The query has to be adopted to the requirements of the encrypted schemes. While adopting the query, an encrypted index structure might be created and tested. After the creation of the encrypted index and the adoption of the query, a user should be able to query the encrypted spatial data using kNN. If a point of interes matches the kNN query, it will be returned to the user. The user should now able to decrypt the result. Finally, the efficiency of the query should be tested and the security should be evaluated. Topic Description adopt a kNN query to the encrypted graph setting if necessary, implement an encrypted index structure implement the protocol evaluate the result regarding efficiency and security Requirements Good general programming skills (Rust, Java or Python) Interest in Cryptography Ability to work self-directed and systematically The thesis can be written in English or German. Contact Georg Bramm Telefon: +49 89 322-9986-147 E-Mail: georg.bramm@aisec.fraunhofer.de Fraunhofer Research Institution for Applied and Integrated Security (AISEC) Service & Application Security Lichtenbergstrasse 11, 85748 Garching (near Munich), Germany https://www.aisec.fraunhofer.de Ausschreibungsdatum: 19. November 2019
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