DynaPro: Dynamic Wireless Sensor Network Data Protection Algorithm in IoT via Differential Privacy

Abstract

With the advent of the era of intelligent Internet of Things (IoT), more and more personal information are collected in the process of deploying IoT in various domains. This brings the problem of data protection in IoT. To address this problem, we propose a data protection algorithm, called DynaPro, based on differential privacy for dynamic wireless sensor networks (WSN), which is the sensor layer of IoT. DynaPro has addressed two issues in data protection of wireless sensor networks. The first issue is the dynamic topology of the network. In order to solve this problem, DynaPro has adopted methods like time window, hierarchical sampling, and graph similarity to process the snapshots of the dynamic network topology. The second issue is addition of noise in differential privacy. To address this issue, DynaPro uses Hierarchical Random Graph (HRG) as middleware to apply differential privacy protection. Instead of adding noise to network data and topology directly, DynaPro adds noise to HRG. In this way, DynaPro can hide the network topology but retain the necessary structural information to support data analysis. Theoretical analysis and experimental results show that DynaPro can preserve the important network features of the original network topology under the premise of the differential privacy protection model.

A condition-based distributed approach for secured privacy preservation of nodes in wireless sensor networks IoT

“…The unique lightweight approach for privacy protection presented in Zheng et al [22] is used to construct two non-colluding cloud platforms and develop a homomorphic cryptosystem. Li et al [23] presents a novel strategy to disguise-based data poisoning attack (DDPA). It is determined to use a method in which the negative characteristics are masked to conceal the processes used to uncover the truth.…”

OELB - IH Algorithm for Secure Data Routing to Improve the Network Location Advisory Privacy Performance in WSN

“…Both are used in EnhAnced Protocol for Source location (EAPS) [1], to adjust the radius of contamination during angle-based and efficient routing. DynaPro [2], as a middleware for application for differential privacy, uses a Hierarchical Random Graph (HRG). Instead, because to add a noise directly to the network of data and topology, DynaPro of noise, add the HRG.…”

Current Research Trends in IoT Security: A Systematic Mapping Study

“…us, privacy preservation is becoming more important [77][78][79]. In addition, intelligent IoT applications enhanced with cloud, edge, and fog computing increasingly deal with personal information to provide intelligent services, and many studies on personal information protection and data protection are being conducted [80][81][82][83]. Among the personal information protection approaches, differential privacy is gaining attention as a mechanism to provide intelligent services by grasping user behavior patterns without infringing on personal information by adding noise to prevent the identification of personal information [81,[84][85][86][87][88].…”