Abstract
IoT devices enhance efficiency, accuracy and economic advantages along with less involvement of human resources, thus our different daily applications have become more flexible and convenient. But, in IoT we have many security and privacy challenges emerging on regular basis. Earlier this issue has been addressed by introduction of many approaches to achieve privacy-preserving in data aggregation process. In this aspect this paper presents an outline of IoT-oriented approach for achieving privacy preservation together with minimizing communication overhead. This paper reviews the latest Privacy Preserving Data Aggregation (PPDA) techniques along with their comparative analysis. Latest techniques are investigated here to give a detail analysis of the each and every step of these techniques. In addition, every mathematical operation used in several PPDA schemes are analyzed here. Also current study will be advantageous to researchers in designing solutions in terms of energy efficiency and computational feasibility for ensuring user privacy in different IoT application
Highlights
In modern age of computing, Internet of Things has been an important technology
Sensor node and sensor network life can be increased with efficient data aggregation approach, since this one reduces communication overhead along with each node’s computation in network
An energy efficient data aggregation method is designed by Othman et al [8] for data privacy and integrity which is secure against node compromise attack
Summary
In modern age of computing, Internet of Things has been an important technology. IoT is an interaction of internet connected smart entities. In order to accomplish these issues, it must have certain features such as Privacy-Preserving and data aggregation [1]. Data aggregation is a method introduced in IoT for significant reduction of sensor node’s energy usage along with communication overhead in data collection development. In data aggregation privacy preservation is a major challenge, where aggregators required performing few aggregation operations on received sensing data. Sensor node and sensor network life can be increased with efficient data aggregation approach, since this one reduces communication overhead along with each node’s computation in network. An efficient privacy-preserving data aggregation method is discussed for IoT. An analysis is presented for privacy-preserving data aggregation in IoT. We have organized the paper as; section 2 discuss PPDA methods in resource-constrained sensor nodes, section 3 gives. Manas Ranjan Mohapatra et al, International Journal of Advanced Research in Computer Science, 11 (5), September-October 2020,17-19 an analysis of these methods and at last, section 4 concludes our discussion
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