Knowledge modeling for privacy-by-design in smart surveillance solution
As new information and communications systems are being equipped with more aggressive capabilities to enable smart surveillance, individuals' private and ethical data is more exposed to potential threats. Consequently, the attention of researchers and policy makers has become increasingly focused on controlling the emerging threats to privacy. In order to ensure that a surveillance system framework complies with the legal, ethical and privacy requirements of the law, in this paper we present a Surveillance Ontology extending the SKOS foundational ontology. The fundamental principles of privacy-by-design (PbD) demand that the surveillance framework consider data minimization, user control, accountability and data separation. Hence, the objective of this ontology is to translate the high-level linguistic rules into the information that can be processed and used to assess the compliance of the video analysis module with the rules defined.