IoT Data Security by Combining Cryptography and Local Differential Privacy

The exponential growth of data collection by IoT devices will continue for many years due to the penetration of cheap high-speed internet connections and increased availability of connectivity in developing countries worldwide. With this, concerns regarding data privacy have increased substantially. The subject of how to securely share data to generate insights among different customers while adhering to confidentiality and ethical and moral guidelines is vital. This study combined local differential privacy with cryptography to transmit the data securely and ensure that confidentiality is preserved even when the data is shared among different parties in the same organization or even when it is transferred outside publically. This experiment compared AES and ChaCha20 to check the performance differences in a resource-constrained environment. The LZ4 algorithm was used to take advantage of compression to save bandwidth and increase encryption speed. This paper also discusses these methods' advantages and disadvantages in detail, and our results demonstrate that these methods can be successfully used to share, store, and transmit data securely.