Secure and Privacy-Enhanced Data Aggregation for IoT Using Fog Computing

Abstract

As the Internet of Things (IoT) expands rapidly, securing sensitive data has become increasingly complex, especially in environments with limited resources and strict latency requirements. By facilitating data processing at the network edge, fog computing minimizes delays and reduces bandwidth consumption. In this paper, we present APPA, which is a method for anonymizing and aggregating Fog-enabled IoT data in a privacy-preserving manner. The APPA provides IoT devices with the ability to choose between privacy-preserving and standard encryption methods based on their privacy preferences and eliminates the need to rely on trusted third parties. As a result of utilizing the Paillier and Bilinear Elagamal’s homomorphic encryption algorithms, the scheme is able to aggregate secure subsets, enable fault-tolerant decryption, and allow dynamic device enrolment and revocation. According to performance evaluations, APPA is significantly more efficient and has a lower communication overhead than existing solutions, thus making it a good choice for scalable and privacy-conscious IoT applications.