Homomorphic Asymmetric Encryption Applied to the Analysis of IoT Communications

Abstract

In this paper, we describe the use of homomorphic encryption techniques in order to not only ensure the data are transmitted in a confidential way, but also to use the encrypted data to provide the manager with statistics that allow them to detect the incorrect functioning of a sensor node or a group of sensors due to either malicious data injection, data transmission, or simply sensor damage (miscalibration, faulty sensor functioning). Obtaining these statistical values does not need decryption, so the process is sped up and can be developed in real time. Operating the data in this way ensures privacy and removes the need to maintain a shared key infrastructure between the sensor nodes and the manager nodes that are part of the blockchain infrastructure. In this work, we focus on operations with the sensor nodes that provide data that will be, later, treated as part of the business logic in the agribusiness sector (for example), hence the importance of having fast checking mechanisms in terms of data quality. The results obtained on conventional configurations of sensor nodes encourage the use of this technique in the aforementioned infrastructure.

A Critical Cybersecurity Analysis and Future Research Directions for the Internet of Things: A Comprehensive Review

“…Symmetric key encryption [134,135] is often used to secure confidential data because of its efficiency and speed. Another kind of encryption used in the IoT is public key encryption [136,137], which uses a pair of keys-a public one for encrypting and a private one for decrypting. Encrypting data with asymmetric keys takes more time, but the private key is never exposed, making this technique safer.…”

A Bootstrapping-Capable Configurable NTT Architecture for Fully Homomorphic Encryption

“…HE can protect sensitive information by allowing the data to be calculated in encrypted form without exposing the raw data [1]. This capability is applicable and important in many sectors that require data privacy as their main priority, such as healthcare [1], finances [2], communications [3], manufacturing [4], and many more.…”