MAPP: A Modular Arithmetic Algorithm for Privacy Preserving in IoT

Abstract

High-speed Internet becomes more widely accessible, the cost of connecting devices is reducing, more devices are being created with Wi-Fi abilities and sensors are built into those devices, technology costs are cost-effective. All of these things are creating a ``storm" for the Internet of Things (IoT) era. With the emergence of the Internet of Things, connect things through internet, there are many devices that are providing data. The more devices, the more data. If these devices want to share data with the aim of achieving abstract knowledge, they need to pass through the network. Some devices provide sensitive information that can be time. We should protect these sensitive data, from unwanted disclosure that is called privacy. In other words, privacy preserving of data is one of the main problems of IoT devices, protecting sensitive data against unauthorized users when we do analysis and even transferring data. To achieve this in this paper, we propose a new method based on modular arithmetic for privacy-preserving when IoT devices produce sensitive time label called MAPP. We applied Number Theory, Modular Arithmetic to achieve that aim. We used CupCarbon 3.0 for simulation and evaluating our proposed method. Performance evaluation shows that our proposed method has good performance from the energy consumption point of view.