Dynamic SSE for storing geospatial data in the cloud

Geo­spa­tial data sets of­ten con­tain sens­it­ive in­form­a­tion, for ex­ample, about urban in­fra­struc­tures. Since clouds are usu­ally provided by third parties, this data needs to be pro­tec­ted. In our pa­per en­titled Dy­namic search­able sym­met­ric en­cryp­tion for stor­ing geo­spa­tial data in the cloud, we present an en­cryp­tion scheme al­low­ing users to en­crypt their data in the cloud and make it search­able at the same time. The pa­per has just been pub­lished to the In­ter­na­tional Journal of In­form­a­tion Se­cur­ity by Springer.

Com­pared to other static en­cryp­tion meth­ods, our ap­proach to search­able sym­met­ric en­cryp­tion (SSE) does not re­quire an ini­tial­iz­a­tion phase. This en­ables users to dy­nam­ic­ally add new data and re­move ex­ist­ing re­cords. In the pa­per, we design mul­tiple pro­to­cols dif­fer­ing in their level of se­cur­ity and per­form­ance, re­spect­ively. All of them sup­port quer­ies con­tain­ing boolean ex­pres­sions, as well as geo­spa­tial quer­ies based on bound­ing boxes, for ex­ample.

Our find­ings in­dic­ate that al­though the search in en­cryp­ted data re­quires more runtime than in un­en­cryp­ted data, our ap­proach is still suit­able for real-world ap­plic­a­tions. We fo­cus on geo­spa­tial data stor­age but our ap­proach can also be ap­plied to ap­plic­a­tions from other areas deal­ing with keyword-based searches in en­cryp­ted data. We con­clude the pa­per with a dis­cus­sion on the be­ne­fits and draw­backs of our ap­proach.


Hiemenz, B., & Krämer, M. (2019). Dy­namic search­able sym­met­ric en­cryp­tion for stor­ing geo­spa­tial data in the cloud. In­ter­na­tional Journal of In­form­a­tion Se­cur­ity, 18(3), 333–354. ht­tps://​doi.org/​10.1007/​s10207-018-0414-4


Ac­cord­ing to Spring­er’s self-archiv­ing policy, you may down­load the manuscript pre-print here. The fi­nal au­then­tic­ated ver­sion is avail­able on the pub­lish­er’s web­site.

Posted by Michel Krämer
on May, 20th 2019.