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Enhancing IoT Healthcare Security with Optimized Edge Computing and Micro Segmentation in Sensor Networks Using KSEWPA and T3FENN
Subramanyam Boyapati, Bhavya Kadiyala, Chaitanya Vasamsetty, Rajani Priya Nippatla, Sunil Kumar Alavilli and Revathi Sundarasekar

The rise of Internet of Things devices in healthcare and sensor networks has greatly improved patient care, but it also brings major security and privacy risks. The existing works failed to detect multi-segment attacks or isolate threats in micro segmented areas. Therefore, this paper presents healthcare security and optimization with edge computing and micro segmentation in sensor networks, and optimized threat detection. Initially, Healthcare devices are registered and device ID is authenticated using UUID. Then the contextual information of the devices is extracted and micro segmentation is done by using CDBRSCAN. Then, for individual micro segments, threat detection and isolation is done by training the model with the dataset followed by feature extraction and from the extracted features the anomaly is detected using T3FENN. From the detected anomaly, behavior profiling takes place by using CDBRSCAN. After behavior profiling, threats are correlated and isolated by using CTCS. Based on the threat detected and its correlation, the access for the device is limited using ITR. At the same time, if there is no anomaly, privacy preservation of the information is done using KSEWPA, which ensures the privacy of sensitive data by using entropy-based weighting and probability measures. Finally, the privacy preserved information is optimized using PSEHO and stored in the cloud server. As per the experimental analysis, the proposed model attained 98.65% accuracy.

Keywords: Universal Unique Identifier (UUID), Contextual Density Based Regularized Spatial Clustering of Applications with Noise (CDBRSCAN), K- Shannon Entropy Weighted Probability Anonymity (KSEWPA), Temporal Feed Forward Feature Encoded Neural Network (T3FENN), Sensor Network, Contextualized Threat Correlation Score (CTCS), Priority Shaping Elk Herd Optimizer (PSEHO), If-Then-Rule (ITR)

DOI: 10.32908/ahswn.v62.15455