Holographic Display in Consumer Electronics for Detecting Abnormal IoT Devices Using a Lightweight Security Model

IoT (Internet of Things) devices are becoming more popular because they can be connected to mobile phones and communicate with various types of devices (e.g., smart homes, automation, and monitoring applications), which provides a high-quality service with the flexibility of performing operations from anywhere at any time. This research proposes a holographic display in consumer electronics to provide a more interactive experience for the user by providing significant security and privacy framework to the IoT devices which are prone to vulnerabilities. A simple Post-Quantum Cryptography Algorithm (PQCA) is used in this study to find flaws in a quantum lattice that is based on a 3x3 matrix in pre-processing. Also, an edge-based anomaly detection framework is created to work with consumer devices to show holographic data streams and IoT device activity in real time for devices with limited resources and less computational overhead than traditional machine learning models. The suggested method conducts testing on a set of unsupervised IoT devices, which contain data and metrics on user behaviour. The dataset contains 8000 service requests in an IoT environment. It finds security anomalies in 70% of the cases in training phases and 30% of the cases in testing phases, respectively. The proposed system detects vulnerable IoT devices by projecting them in a holographic projection graph, which in turn enhances privacy. The test results showed that the minimum encryption time overhead is 0.00085, and the accuracy achieved is about 97.44%.