Enhanced-Blind Approach for Privacy Protection of IoT

The Internet of Thing (IoT) refers to a vast number of things (e.g., sensors) that are connected to the internet to share data such as in smart cities, intelligent transportation, and healthcare. However, these data may be subject to privacy breaching attacks that pose considerable challenges in the development and deployment of IoT. Therefore, many solutions have been introduced with the assumption of trusted parties' inclusion (e.g., Service Providers) to increase the level of privacy. For example, the blind approach solution depends on asymmetric keys in which the third parties anonymize the user's identity before forwarding the encrypted query to the service provider without being able to perusal the transferred data. But, what will happen if the anonymizer sends the request to the service provider itself without the user's knowledge, in this case, it will be able to read the answers and hacking the privacy of the user. In our research, we propose an enhanced technique for the blind approach to enable users to detect any unauthorized access to their data and then take action. A case-study will be presented in the paper to prove the effectiveness of the enhanced technique in addressing the drawback of the main Blind approach and thereby improving the level of user's privacy in IoT.