scholarly journals A Secure Privacy-Preserving Data Aggregation Model in Wearable Wireless Sensor Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Changlun Zhang ◽  
Chao Li ◽  
Jian Zhang
Keyword(s):  
Data Aggregation ◽  
Privacy Preservation ◽  
Rapid Development ◽  
Cluster Head ◽  
Privacy Preserving ◽  
Base Station ◽  
Sensor Nodes ◽  
Mixed Data ◽  
Communication Overhead ◽  
Aggregation Model

With the rapid development and widespread use of wearable wireless sensors, data aggregation technique becomes one of the most important research areas. However, the sensitive data collected by sensor nodes may be leaked at the intermediate aggregator nodes. So, privacy preservation is becoming an increasingly important issue in security data aggregation. In this paper, we propose a security privacy-preserving data aggregation model, which adopts a mixed data aggregation structure. Data integrity is verified both at cluster head and at base station. Some nodes adopt slicing technology to avoid the leak of data at the cluster head in inner-cluster. Furthermore, a mechanism is given to locate the compromised nodes. The analysis shows that the model is robust to many attacks and has a lower communication overhead.

scholarly journals Irrelevant data elimination based on a k-means clustering algorithm for efficient data aggregation and human activity classification in smart home sensor networks

2020 ◽  
Vol 16 (6) ◽  
pp. 155014772092982
Author(s):  
Siriporn Pattamaset ◽  
Jae Sung Choi
Keyword(s):  
Human Activity ◽  
Data Aggregation ◽  
Smart Home ◽  
Clustering Algorithm ◽  
Cluster Head ◽  
Original Data ◽  
Base Station ◽  
Sensor Nodes ◽  
Activity Classification ◽  
Successful Operation

For the successful operation of smart home environments, it is important to know the state or activity of an occupant. A large number of sensors can be deployed and embedded in places or things. All sensor nodes measure the physical world and send data to the base station for processing. However, the processing of all collected data from every sensor node can consume significant energy and time. In order to enhance the sensor network in smart home applications, we propose the irrelevant data elimination based on k-means clustering algorithm to enhance data aggregation. This approach embeds the cluster head–based algorithm into cluster heads to omit irrelevant data from the base station. The pattern of measured data in each room can be clustered as an active pattern when human activity happens in that room and a stable pattern when human activity does not happen in the room. The irrelevant data elimination based on k-means clustering algorithm approach can reduce 55.94% of the original data with similar results in human activity classification. This study proves that the proposed approach can eliminate meaningless data and intelligently aggregate data by delivering only data from rooms in which human activity likely occurs.

scholarly journals MCEEP-BDA: Multilevel Clustering Based -Energy Efficient Privacy-Preserving Big Data Aggregation in Large-Scale Wsn

2019 ◽  
Vol 9 (1) ◽  
pp. 6779-6785
Keyword(s):  
Big Data ◽  
Data Storage ◽  
Data Aggregation ◽  
Energy Efficient ◽  
Large Scale ◽  
Computational Cost ◽  
Privacy Preserving ◽  
Sensor Nodes ◽  
Sensor Data ◽  
Communication Overhead

In current scenario, the Big Data processing that includes data storage, aggregation, transmission and evaluation has attained more attraction from researchers, since there is an enormous data produced by the sensing nodes of large-scale Wireless Sensor Networks (WSNs). Concerning the energy efficiency and the privacy conservation needs of WSNs in big data aggregation and processing, this paper develops a novel model called Multilevel Clustering based- Energy Efficient Privacy-preserving Big Data Aggregation (MCEEP-BDA). Initially, based on the pre-defined structure of gradient topology, the sensor nodes are framed into clusters. Further, the sensed information collected from each sensor node is altered with respect to the privacy preserving model obtained from their corresponding sinks. The Energy model has been defined for determining the efficient energy consumption in the overall process of big data aggregation in WSN. Moreover, Cluster_head Rotation process has been incorporated for effectively reducing the communication overhead and computational cost. Additionally, algorithm has been framed for Least BDA Tree for aggregating the big sensor data through the selected cluster heads effectively. The simulation results show that the developed MCEEP-BDA model is more scalable and energy efficient. And, it shows that the Big Data Aggregation (BDA) has been performed here with reduced resource utilization and secure manner by the privacy preserving model, further satisfying the security concerns of the developing application-oriented needs.

scholarly journals Efficient organization of nodes in wireless sensor networks (clustering location-based LEACH)

2022 ◽  
Vol 12 (1) ◽  
pp. 1011
Author(s):  
Mohammed Réda El Ouadi ◽  
Abderrahim Hasbi
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Rapid Development ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Main Element

The rapid development of connected devices and wireless communication has enabled several researchers to study wireless sensor networks and propose methods and algorithms to improve their performance. Wireless sensor networks (WSN) are composed of several sensor nodes deployed to collect and transfer data to base station (BS). Sensor node is considered as the main element in this field, characterized by minimal capacities of storage, energy, and computing. In consequence of the important impact of the energy on network lifetime, several researches are interested to propose different mechanisms to minimize energy consumption. In this work, we propose a new enhancement of low-energy adaptive clustering hierarchy (LEACH) protocol, named clustering location-based LEACH (CLOC-LEACH), which represents a continuity of our previous published work location-based LEACH (LOC-LEACH). The proposed protocol organizes sensor nodes into four regions, using clustering mechanism. In addition, an efficient concept is adopted to choose cluster head. CLOC-LEACH considers the energy as the principal metric to choose cluster heads and uses a gateway node to ensure the inter-cluster communication. The simulation with MATLAB shows that our contribution offers better performance than LEACH and LOC-LEACH, in terms of stability, energy consumption and network lifetime.

scholarly journals Query Privacy Preserving for Data Aggregation in Wireless Sensor Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-10 ◽  
Author(s):  
X. Liu ◽  
X. Zhang ◽  
J. Yu ◽  
C. Fu
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Data Privacy ◽  
Homomorphic Encryption ◽  
Privacy Preserving ◽  
Sensor Nodes ◽  
Experimental Simulation ◽  
Wireless Sensor ◽  
Communication Overhead

Wireless Sensor Networks (WSNs) are increasingly involved in many applications. However, communication overhead and energy efficiency of sensor nodes are the major concerns in WSNs. In addition, the broadcast communication mode of WSNs makes the network vulnerable to privacy disclosure when the sensor nodes are subject to malicious behaviours. Based on the abovementioned issues, we present a Queries Privacy Preserving mechanism for Data Aggregation (QPPDA) which may reduce energy consumption by allowing multiple queries to be aggregated into a single packet and preserve data privacy effectively by employing a privacy homomorphic encryption scheme. The performance evaluations obtained from the theoretical analysis and the experimental simulation show that our mechanism can reduce the communication overhead of the network and protect the private data from being compromised.

scholarly journals Location Privacy-Preserving Method Based on Historical Proximity Location

2020 ◽  
Vol 2020 ◽  
pp. 1-16 ◽  
Author(s):  
Xueying Guo ◽  
Wenming Wang ◽  
Haiping Huang ◽  
Qi Li ◽  
Reza Malekian
Keyword(s):  
Mobile Communications ◽  
Privacy Preservation ◽  
Location Privacy ◽  
Rapid Development ◽  
Main Idea ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Communication Overhead ◽  
Server Side ◽  
Current Location

With the rapid development of Internet services, mobile communications, and IoT applications, Location-Based Service (LBS) has become an indispensable part in our daily life in recent years. However, when users benefit from LBSs, the collection and analysis of users’ location data and trajectory information may jeopardize their privacy. To address this problem, a new privacy-preserving method based on historical proximity locations is proposed. The main idea of this approach is to substitute one existing historical adjacent location around the user for his/her current location and then submit the selected location to the LBS server. This method ensures that the user can obtain location-based services without submitting the real location information to the untrusted LBS server, which can improve the privacy-preserving level while reducing the calculation and communication overhead on the server side. Furthermore, our scheme can not only provide privacy preservation in snapshot queries but also protect trajectory privacy in continuous LBSs. Compared with other location privacy-preserving methods such as k-anonymity and dummy location, our scheme improves the quality of LBS and query efficiency while keeping a satisfactory privacy level.

scholarly journals Node Security in Hierarchical Sensor Networks: Distribution of Functions versus Keys

2009 ◽  
Vol 5 (5) ◽  
pp. 531-556
Author(s):  
Biswajit Panja ◽  
Sanjay Madria
Keyword(s):  
Sensor Networks ◽  
Sensor Network ◽  
Data Aggregation ◽  
Secure Communication ◽  
Cluster Head ◽  
Key Distribution ◽  
Base Station ◽  
Sensor Nodes ◽  
Cluster Heads ◽  
Dynamic Cluster

Secure communication involving cluster heads in a sensor network is vital as they are responsible for data aggregation and for taking important decisions in their groups. In this article, we propose a scheme for secure communication via such nodes in a sensor network. In our approach, the base station provides a function to the cluster head of each group, which is used to compute the key for the secure communication with the base station. The protocol is first elucidated for a fixed cluster head in each group and later it is extended for dynamic cluster heads. Each function is computed using a certain number of points on the curve using Lagrange's interpolation [ 10 ]. The curve computed from the function intersects the Y axis at a point which is considered as the key of the cluster head. The advantage of this approach in providing secure communication out of a cluster head is that an adversary will not be able to get hold of the function by attacking the cluster head alone. This is because instead of storing the function in the cluster head, sub-functions are generated and distributed among the sensor nodes in each group. After the distribution of the sub-functions, these functions are discarded from each cluster head. When a cluster head wants to communicate with the base station it accumulates sub-functions to compute the function to compute the key used to encrypt/decrypt messages sent and received to and from the base station. For updating the functions, the sub-functions are updated using the information provided by the base station. The key distribution approach requires that the function is to be kept secret all the time. However, since it is present in the cluster head to compute the key, it is difficult to ensure its security. We have experimentally evaluated our scheme through the simulations using TinyOs and TOSSIM and the results show that latency can be improved by using the sub-functions updating approach rather than re-generating the functions and the sub-functions. Also, updating the sub-functions requires reduced computation and bandwidth requirements than updating the sub-keys because updating of the keys needs to be done from scratch whereas updating of the sub-functions are done using an updating parameter.

An optimal data aggregation technique for physics-based applications

2018 ◽  
Vol 32 (25) ◽  
pp. 1850297 ◽  
Author(s):  
Upasna Joshi ◽  
Rajiv Sharma
Keyword(s):  
Data Aggregation ◽  
Energy Efficient ◽  
Power Level ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Neighborhood Search ◽  
Energy Efficient Routing ◽  
Sleep State ◽  
Cluster Heads

In wireless sensor network (WSN), most of the devices function on batteries. These nodes or devices have inadequate amount of initial energy which are consumed at diverse rates, based on the power level and intended receiver. In sleep scheduling algorithms, most of the sensor nodes are turned to sleep state to preserve energy and improve the network lifetime (NL). In this paper, an energy-efficient dynamic cluster-based protocol is proposed for WSN especially for physics-based applications. Initially, the network is divided into small clusters using adaptive clustering. The clusters are managed by the cluster heads. The cluster heads are elected based on the novel dynamic threshold. Afterwards, general variable neighborhood search is used to obtain the energy-efficient paths for inter-cluster data aggregation which is used to communicate with the sink. The performance of the proposed method is compared with competitive energy-efficient routing protocols in terms of various factors such as stable period, NL, packets sent to base station and packets sent to cluster head. Extensive experiments prove that the proposed protocol provides higher NL than the existing protocols.

Performance Analysis of RNC Clustering Protocol in Wireless Sensor Network

2019 ◽  
Vol 10 ◽  
Author(s):  
Piyush Rawat ◽  
Siddhartha Chauhan
Keyword(s):  
Energy Consumption ◽  
Network Performance ◽  
Energy Levels ◽  
Cluster Head ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Threshold Function ◽  
Efficient Manner ◽  
Clustering Protocol

Background and Objective: The functionalities of wireless sensor networks (WSN) are growing in various areas, so to handle the energy consumption of network in an efficient manner is a challenging task. The sensor nodes in the WSN are equipped with limited battery power, so there is a need to utilize the sensor power in an efficient way. The clustering of nodes in the network is one of the ways to handle the limited energy of nodes to enhance the lifetime of the network for its longer working without failure. Methods: The proposed approach is based on forming a cluster of various sensor nodes and then selecting a sensor as cluster head (CH). The heterogeneous sensor nodes are used in the proposed approach in which sensors are provided with different energy levels. The selection of an efficient node as CH can help in enhancing the network lifetime. The threshold function and random function are used for selecting the cluster head among various sensors for selecting the efficient node as CH. Various performance parameters such as network lifespan, packets transferred to the base station (BS) and energy consumption are used to perform the comparison between the proposed technique and previous approaches. Results and Discussion: To validate the working of the proposed technique the simulation is performed in MATLAB simulator. The proposed approach has enhanced the lifetime of the network as compared to the existing approaches. The proposed algorithm is compared with various existing techniques to measure its performance and effectiveness. The sensor nodes are randomly deployed in a 100m*100m area. Conclusion: The simulation results showed that the proposed technique has enhanced the lifespan of the network by utilizing the node’s energy in an efficient manner and reduced the consumption of energy for better network performance.

scholarly journals Energy Consumption Based Low Energy Aware Gateway (LEAG) Protocol in Wireless Sensor Networks

2019 ◽  
Vol 8 (5S3) ◽  
pp. 128-132 ◽  
Keyword(s):  
Wireless Sensor Networks ◽  
Energy Consumption ◽  
Sensor Networks ◽  
Cluster Head ◽  
Base Station ◽  
Low Energy ◽  
Secure Routing ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Energy Aware

Wireless Sensor Networks (WSN) consists of a large amount of nodes connected in a self-directed manner. The most important problems in WSN are Energy, Routing, Security, etc., price of the sensor nodes and renovation of these networks is reasonable. The sensor node tools included a radio transceiver with an antenna and an energy source, usually a battery. WSN compute the environmental conditions such as temperature, sound, pollution levels, etc., WSN built the network with the help of nodes. A sensor community consists of many detection stations known as sensor nodes, every of which is small, light-weight and portable. Nodes are linked separately. Each node is linked into the sensors. In recent years WSN has grow to be an essential function in real world. The data’s are sent from end to end multiple nodes and gateways, the data’s are connected to other networks such as wireless Ethernet. MGEAR is the existing mechanism. It works with the routing and energy consumption. The principal problem of this work is choosing cluster head, and the selection is based on base station, so the manner is consumes energy. In this paper, develop the novel based hybrid protocol Low Energy Aware Gateway (LEAG). We used Zigbee techniques to reduce energy consumption and routing. Gateway is used to minimize the energy consumption and data is send to the base station. Nodes are used to transmit the data into the cluster head, it transmit the data into gateway and gateway compress and aggregate the data then sent to the base station. Simulation result shows our proposed mechanism consumes less energy, increased throughput, packet delivery ration and secure routing when compared to existing mechanism (MGEAR).

scholarly journals An Energy Efficient Secure Data Aggregation in Wireless Sensor Networks

2021 ◽  
Author(s):  
Jenice Prabu A ◽  
Hevin Rajesh D
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Data Aggregation ◽  
Data Communication ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Delivery Ratio ◽  
Malicious Nodes ◽  
Aggregated Data

Abstract In Wireless sensor network, the major issues are security and energy consumption. There may be several numbers of malicious nodes present in sensor networks. Several techniques have been proposed by the researchers to identify these malicious nodes. WSNs contain many sensor nodes that sense their environment and also transmit their data via multi-hop communication schemes to the base station. These sensor nodes provides power supply using battery and the energy consumption of these batteries must be low. Securing the data is to avoid attacks on these nodes and data communication. The aggregation of data helps to minimize the amount of messages transmitted within the network and thus reduces overall network energy consumption. Moreover, the base station may distinguish the encrypted and aggregated data based on the encryption keys during the decryption of the aggregated data. In this paper, two aspects of the problem is concerned, we investigate the efficiency of data aggregation: first, how to develop cluster-based routing algorithms to achieve the lowest energy consumption for aggregating data, and second, security issues in wsn. By using Network simulator2 (NS2) this scheme is simulated. In the proposed scheme, energy consumption, packet delivery ratio and throughput is analyzed. The proposed clustering, routing, and protection protocol based on the MCSDA algorithm shows significant improvement over the state-of - the-art protocol.

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