Secured data aggregation in wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (3) ◽  
pp. 369-375 ◽  
Author(s):  
Sathya D. ◽  
Ganesh Kumar P.
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Computation Time ◽  
Wireless Sensor ◽  
Content Type ◽  
Homomorphic Cryptosystem ◽  
Secured Data ◽  
Time And Energy

PurposeThis study aims to provide a secured data aggregation with reduced energy consumption in WSN. Data aggregation is the process of reducing communication overhead in wireless sensor networks (WSNs). Presently, securing data aggregation is an important research issue in WSNs due to two facts: sensor nodes deployed in the sensitive and open environment are easily targeted by adversaries, and the leakage of aggregated data causes damage in the networks, and these data cannot be retrieved in a short span of time. Most of the traditional cryptographic algorithms provide security for data aggregation, but they do not reduce energy consumption.Design/methodology/approachNowadays, the homomorphic cryptosystem is used widely to provide security with low energy consumption, as the aggregation is performed on the ciphertext without decryption at the cluster head. In the present paper, the Paillier additive homomorphic cryptosystem and Bonehet al.’s aggregate signature method are used to encrypt and to verify aggregate data at the base station.FindingsThe combination of the two algorithms reduces computation time and energy consumption when compared with the state-of-the-art techniques.Practical implicationsThe secured data aggregation is useful in health-related applications, military applications, etc.Originality/valueThe new combination of encryption and signature methods provides confidentiality and integrity. In addition, it consumes less computation time and energy consumption than existing methods.

scholarly journals Hierarchical classification of time series data aggregation in underwater wireless sensor networks

2020 ◽  
Vol 37 (2) ◽  
pp. 53-64
Author(s):  
Durairaj Ruby ◽  
Jayachandran Jeyachidra
Keyword(s):  
Time Series ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Error Rate ◽  
Data Aggregation ◽  
Hierarchical Classification ◽  
Wireless Sensor ◽  
Underwater Wireless Sensor Networks

Environmental fluctuations are continuous and provide opportunities for further exploration, including the study of overground, as well as underground and submarine, strata. Underwater wireless sensor networks (UWSNs) facilitate the study of ocean-based submarine and marine parameters details and data. Hardware plays a major role in monitoring marine parameters; however, protecting the hardware deployed in water can be difficult. To extend the lifespan of the hardware, the inputs, processing and output cycles may be reduced, thus minimising the consumption of energy and increasing the lifespan of the devices. In the present study, time series similarity check (TSSC) algorithm is applied to the real-time sensed data to identify repeated and duplicated occurrences of data for reduction, and thus improve energy consumption. Hierarchical classification of ANOVA approach (HCAA) applies ANOVA (analysis of variance) statistical analysis model to calculate error analysis for realtime sensed data. To avoid repeated occurrences, the scheduled time to read measurements may be extended, thereby reducing the energy consumption of the node. The shorter time interval of observations leads to a higher error rate with lesser accuracy. TSSC and HCAA data aggregation models help to minimise the error rate and improve accuracy.

Cluster Trisecting Based Data Aggregation Scheme for Wireless Sensor Networks

2013 ◽  
Vol 756-759 ◽  
pp. 1126-1130
Author(s):  
Jiang Hong Guo ◽  
De Li Chen
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Wireless Sensor ◽  
Important Method ◽  
Cluster Aggregation ◽  
Aggregation Scheme ◽  
Reduce Energy Consumption

Data aggregation is an important method to reduce energy consumption in wireless sensor networks (WSN). Auth-ors proposed a cluster trisecting based data aggregation scheme for wireless sensor networks in which the cluster was trisected and some reporters were assigned to each region. The nodes have same reading and located in same region with reporter will keep silent in data aggregating, thus reducing the inner-cluster transmissions. Analysis and simulation show that the transmissions of inner-cluster aggregation in our scheme lower than that of related schemes and the decrease of trans-missions is obvious when redundancy of sensor readings is high.

scholarly journals A DISTRIBUTED ENERGY EFFICIENT CLUSTERING ALGORITHM FOR DATA AGGREGATION IN WIRELESS SENSOR NETWORKS

2018 ◽  
Vol 19 (1) ◽  
pp. 72-90
Author(s):  
Seyed Mohammad Bagher Musavi Shirazi ◽  
Maryam Sabet ◽  
Mohammad Reza Pajoohan
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Clustering Algorithm ◽  
Base Station ◽  
Wireless Sensor ◽  
Relay Nodes ◽  
Cluster Heads ◽  
Energy Efficient Clustering

Wireless sensor networks (WSNs) are a new generation of networks typically consisting of a large number of inexpensive nodes with wireless communications. The main purpose of these networks is to collect information from the environment for further processing. Nodes in the network have been equipped with limited battery lifetime, so energy saving is one of the major issues in WSNs. If we balance the load among cluster heads and prevent having an extra load on just a few nodes in the network, we can reach longer network lifetime. One solution to control energy consumption and balance the load among nodes is to use clustering techniques. In this paper, we propose a new distributed energy-efficient clustering algorithm for data aggregation in wireless sensor networks, called Distributed Clustering for Data Aggregation (DCDA). In our new approach, an optimal transmission tree is constructed among sensor nodes with a new greedy method. Base station (BS) is the root, cluster heads (CHs) and relay nodes are intermediate nodes, and other nodes (cluster member nodes) are the leaves of this transmission tree. DCDA balances load among CHs in intra-cluster and inter-cluster data communications using different cluster sizes. For efficient inter-cluster communications, some relay nodes will transfer data between CHs. Energy consumption, distance to the base station, and cluster heads’ centric metric are three main adjustment parameters for the cluster heads election. Simulation results show that the proposed protocol leads to the reduction of individual sensor nodes’ energy consumption and prolongs network lifetime, in comparison with other known methods. ABSTRAK: Rangkaian sensor wayarles (WSN) adalah rangkaian generasi baru yang terdiri daripada nod-nod murah komunikasi wayarles. Tujuan rangkaian-rangkaian ini adalah bagi mengumpul maklumat sekeliling untuk proses seterusnya. Nod dalam rangkaian ini dilengkapi bateri kurang jangka hayat, jadi simpanan tenaga adalah satu isu besar dalam WSN. Jika beban diimbang antara induk kelompok dan lebihan beban dihalang pada setiap rangkaian iaitu hanya sebilangan kecil nod pada tiap-tiap kelompok,  jangka hayat dapat dipanjangkan pada sesebuah rangkaian. Satu penyelesaian adalah dengan mengawal penggunaan tenaga dan mengimbangi beban antara nod menggunakan teknik berkelompok. Kajian ini mencadangkan kaedah baru pembahagian tenaga berkesan secara algoritma berkelompok bagi pembahagian data dalam WSN, dikenali sebagai Pembahagian Kelompok Kumpulan Data (DCDA). Melalui pendekatan baru ini, pokok transmisi optimum dibina antara nod sensor melalui kaedah baru. Stesen utama (BS) ialah akar, induk kelompok-kelompok (CHs) dan nod penyiar ialah nod perantara, dan nod-nod lain (nod-nod ahli kelompok) ialah daun bagi pokok trasmisi. DCDA mengimbangi beban CHs antara-kelompok dan dalam-kelompok komunikasi data daripada kelompok berbeza saiz. Bagi komunikasi berkesan dalam-kelompok, sebahagian nod penyampai akan memindahkan data antara CHs. Penggunaan tenaga, jarak ke stesen utama dan induk kelompok metrik sentrik adalah tiga parameter pelaras bagi pemilihan induk kelompok. Keputusan simulasi protokol yang dicadang menunjukkan pengurangan penggunaan tenaga pada nod-nod sensor individu dan memanjangkan jangka hayat rangkaian, berbanding kaedah-kaedah lain yang diketahui.

scholarly journals SECURED DATA AGGREGATION METHODS IN WIRELESS SENSOR NETWORKS USING HOMOMORPHIC OPERATION - A REVIEW

2017 ◽  
Vol 10 (13) ◽  
pp. 328
Author(s):  
Shahina K ◽  
Vaidehi Vijayakumar
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Homomorphic Encryption ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Issues ◽  
Aggregation Methods ◽  
Energy Constrained ◽  
Secured Data

Wireless sensor networks are energy constrained. Data aggregation is an important mechanism for achieving energy efficiency in such networks. The aggregation reduces redundancy in data transmission which results in improved energy usage. Several security issues are there in data aggregation, which includes data confidentiality, data integrity, availability, and freshness. Such issues become complex since WSN is deployed in hostile and unattended environment. So the sensor nodes may fail and compromised by adversaries. Secured data aggregation in sensor network is a topic of research.  Many solutions are proposed for secured data aggregation, using different encryption methods. Homomorphic encryption is one of such technique. In homomorphic encryption, all the nodes participate in the aggregation. Here, nodes can’t see any intermediate or final result but the aggregation is efficient. In this paper, secured data aggregation methods are classified and the performance is compared in terms of integrity and confidentiality.

An Approach to Secure Data Aggregation in Wireless Sensor Networks (WSN) using Asymmetric Homomorphic Encryption (Elliptic Curve Cryptography) Scheme

2017 ◽  
Vol 7 (7) ◽  
pp. 263
Author(s):  
Md Sirajul Huque ◽  
Sk. Bhadar Saheb ◽  
Jayaram Boga
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Elliptic Curve ◽  
Sensor Network ◽  
Data Aggregation ◽  
Elliptic Curve Cryptography ◽  
Base Station ◽  
Wireless Sensor ◽  
Secure Data Aggregation ◽  
Secured Data

Wireless sensor networks (WSN) are a collection of autonomous collection of motes. Sensor motes are usually Low computational and low powered. In WSN Sensor motes are used to collect environmental data collection and pass that data to the base station. Data aggregation is a common technique widely used in wireless sensor networks. [2] Data aggregation is the process of collecting the data from multiple sensor nodes by avoiding the redundant data transmission and that collected data has been sent to the base station (BS) in single route. Secured data aggregation deals with Securing aggregated data collected from various sources. Many secured data aggregation algorithms has been proposed by many researchers. Symmetric key based cryptography schemes are not suitable when wireless sensor network grows. Here we are proposing an approach to secured data aggregation in wireless sensor networks using Asymmetric key based Elliptic Curve cryptography technique. Elliptic curve cryptography (ECC) [1] is an approach to public-key cryptography based on the algebraic structure of elliptic curves over finite fields. Elliptic Curve Cryptography requires smaller keys compared to non-Elliptic curve cryptography (based on plain Galois fields) to provide equivalent security. The proposed technique of secure data aggregation is used to improve the sensor network lifetime and to reduce the energy consumption during aggregation process.

A novel double sparse structure dictionary learning–based compressive data-gathering algorithm in wireless sensor networks

Sensor Review ◽  
2021 ◽  
Vol 41 (1) ◽  
pp. 65-73
Author(s):  
Junying Chen ◽  
Zhanshe Guo ◽  
Fuqiang Zhou ◽  
Jiangwen Wan ◽  
Donghao Wang
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Sparse Representation ◽  
Dictionary Learning ◽  
Data Gathering ◽  
Experimental Results ◽  
Wireless Sensor ◽  
Learning Stage ◽  
Content Type

Purpose As the limited energy of wireless sensor networks (WSNs), energy-efficient data-gathering algorithms are required. This paper proposes a compressive data-gathering algorithm based on double sparse structure dictionary learning (DSSDL). The purpose of this paper is to reduce the energy consumption of WSNs. Design/methodology/approach The historical data is used to construct a sparse representation base. In the dictionary-learning stage, the sparse representation matrix is decomposed into the product of double sparse matrices. Then, in the update stage of the dictionary, the sparse representation matrix is orthogonalized and unitized. The finally obtained double sparse structure dictionary is applied to the compressive data gathering in WSNs. Findings The dictionary obtained by the proposed algorithm has better sparse representation ability. The experimental results show that, the sparse representation error can be reduced by at least 3.6% compared with other dictionaries. In addition, the better sparse representation ability makes the WSNs achieve less measurement times under the same accuracy of data gathering, which means more energy saving. According to the results of simulation, the proposed algorithm can reduce the energy consumption by at least 2.7% compared with other compressive data-gathering methods under the same data-gathering accuracy. Originality/value In this paper, the double sparse structure dictionary is introduced into the compressive data-gathering algorithm in WSNs. The experimental results indicate that the proposed algorithm has good performance on energy consumption and sparse representation.

Genetic optimization of hybrid clustering algorithm in mobile wireless sensor networks

Sensor Review ◽  
2018 ◽  
Vol 38 (4) ◽  
pp. 526-533 ◽  
Author(s):  
Sangeetha M. ◽  
Sabari A.
Keyword(s):  
Genetic Algorithm ◽  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Clustering Algorithm ◽  
Wireless Sensor ◽  
Mobile Wireless ◽  
Content Type ◽  
Mobile Wireless Sensor

Purpose This paper aims to provide a prolonging network lifetime and optimizing energy consumption in mobile wireless sensor networks (MWSNs). MWSNs have characteristics of dynamic topology due to the factors such as energy consumption and node movement that lead to create a problem in lifetime of the sensor network. Node clustering in wireless sensor networks (WSNs) helps in extending the network life time by reducing the nodes’ communication energy and balancing their remaining energy. It is necessary to have an effective clustering algorithm for adapting the topology changes and improve the network lifetime. Design/methodology/approach This work consists of two centralized dynamic genetic algorithm-constructed algorithms for achieving the objective in MWSNs. The first algorithm is based on improved Unequal Clustering-Genetic Algorithm, and the second algorithm is Hybrid K-means Clustering-Genetic Algorithm. Findings Simulation results show that improved genetic centralized clustering algorithm helps to find the good cluster configuration and number of cluster heads to limit the node energy consumption and enhance network lifetime. Research limitations/implications In this work, each node transmits and receives packets at the same energy level throughout the solution. The proposed approach was implemented in centralized clustering only. Practical implications The main reason for the research efforts and rapid development of MWSNs occupies a broad range of circumstances in military operations. Social implications The research highly gains impacts toward mobile-based applications. Originality/value A new fitness function is proposed to improve the network lifetime, energy consumption and packet transmissions of MWSNs.

scholarly journals Detecting malicious nodes using data aggregation protocols in wireless sensor networks

2017 ◽  
Vol 7 (1.1) ◽  
pp. 594
Author(s):  
P. Balamurugan ◽  
M. Shyamala Devi ◽  
V. Sharmila
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Transmission ◽  
Data Aggregation ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Destination Node ◽  
Malicious Nodes ◽  
Secured Data

At present scenario, sensor devices are used in various fields for gathering information so all those data should be secured safely. Securing data is an important role in Wireless Sensor Networks (WSN). WSN is extremely essential for the purpose of reducing the complete redundancy and energy consumption during gathering data among sensor nodes. Optimized data aggregation is needed at cluster head and Base Station (BS) for secured data transmission. Data aggregation is performed in all routers while forwarding data from source to destination node. The complete life time of sensor networks is reducing because of using energy inefficient nodes for the purpose of aggregation. So this paper introduces the optimized methods for securing data (OMSD) which is trust based weights and also completely about the attacks and some methods for secured data transmission. 

Sign in / Sign up

Export Citation Format

Share Document