Efficient Security Model for RDF Files Used in IoT Applications

The openness environment of IoT ecosystem arises several security and privacy issues. However, the huge amount of data produced by several IoT devices restricts using traditional security methods. Another security challenge for IoT system is the interoperability between heterogeneous IoT devices. Semantic Web has risen as a promising technology that provides semantic annotations allowing interoperability between IoT devices. Semantic web uses RDF triples to allow semantic data exchange between heterogeneous applications. Hence, RDF files used in IoT systems require specific security mechanism that regards large data size as well as rapidly data updates. The proposed work introduces a security novel that provides RDF files with a fine grained partial encryption. The proposed method allows applying security for the sensitive parts of RDF files without affecting the public parts. Encryption metadata is stored in a container related to each individual sensitive triple. Thus accessing public data in RDF file is not affected with the encryption overheads. A motivation scenario for privacy in a smart city is used to evaluate the proposed method. Experimental results showed that the proposed methodology enhances the access time of RDF triples from 10.4 msec to 6.2 msec. Moreover the proposed method facilitates integration of separated parts of a RDF graph together. The empirical evaluation proved the enhancement in efficiency and flexibility by applying the proposed method to RDF files used in IoT systems. Moreover the insensitive triples in RDF files are not affected with the security overheads.