Secure and energy-efficient data aggregation in Wireless Sensor Networks

Abstract

Abstract-Data aggregation in intermediate nodes (called aggregator nodes)is an effective approach for optimizing consumption of scarce resources like bandwidth and energy in Wireless Sensor Networks (WSNs). However, in-network processing poses a problem for the privacy of the sensor data since individual data of sensor nodes need to be known to the aggregator node before the aggregation process can be carried out.In applications of WSNs, privacy-preserving data aggregation has become an important requirement due to sensitive nature of the sensor data. Researchers have proposed a number of protocols and schemes for this purpose. He et al. (INFOCOM 2007) have proposed a protocol -called CPDA -for carrying out additive data aggregation in a privacy-preserving manner for application in WSNs. The scheme has been quite popular and well-known. In spite of the popularity of this protocol, it has been found that the protocol is vulnerable to attack and it is also not energy-efficient. In this paper, we first present a brief state of the art survey on the current privacypreserving data aggregation protocols for WSNS. Then we describe the CPDA protocol and identify its security vulnerability. Finally, we demonstrate how the protocol can be made secure and energy efficient.

Energy Efficient Auto Protecting Nodes in Secured Data Transmission in Mobile Ad-Hoc Networks

“…The objective is to maximizing both network security and lifetime subject to the energy constraints [4][5] [6][7] [8]. As a summary, a three-phase disjoint routing scheme called the Security and Energy-efficient Disjoint Route (SEDR) was proposed.…”

Genetically derived secure cluster‐based data aggregation in wireless sensor networks

“…Sen [16] proposed a secure and energy-efficient data aggregation in WSNs. The vulnerabilities in existing cluster-based private data aggregation (CPDA) protocol is analysed and an enhancement has been made to execute it efficiently against vulnerability and also to make it computationally more efficient.…”