A Novel Bogus Data Detection and Filtering Scheme for Wireless Sensor Networks

2012 ◽  
Vol 531-532 ◽  
pp. 707-711
Author(s):  
Zhi Ming Zhang ◽  
Xiao Yong Xiong ◽  
Chang Gen Jiang
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Savings ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Data Detection ◽  
Security Level ◽  
Forwarding Node ◽  
High Security Level ◽  
Hostile Environments

In many scenarios, wireless sensor networks are deployed in hostile environments. Adversaries could easily compromise sensor node, and bogus data could be injected into the network through the compromised sensor nodes, which decreases the accuracy of the sensing data and wastes scarce energy resources of the networks. In this paper, a novel bogus data detection and filtering scheme for wireless sensor networks was proposed based on one-way hash function. In the proposed scheme, if the sensing node was compromised, the based station could verify the endorsement report, and if the compromised forwarding node modified the report packet, the bogus data could be verified by the next forwarding node, and the modified report packet would be discarded. The analysis shows that the proposed scheme not only provides a high security level but also can detect most bogus data and achieve energy savings.

Secure Deployment with Optimal Connectivity in Wireless Sensor Networks

2020 ◽  
pp. 147-168
Author(s):  
Anju Sangwan ◽  
Rishipal Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Network Size ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Level ◽  
Real Model ◽  
Homogeneous Network ◽  
Basic Issue

In the hostile areas, deployment of the sensor nodes in wireless sensor networks is one of the basic issue to be addressed. The node deployment method has great impact on the performance metrics like connectivity, security and resilience. In this paper, a technique based on strong keying mechanism is proposed which will enhance the security of a non-homogeneous network using the random deployment of the nodes. For this, the q-composite key pre-distribution technique is presented with new flavor that will enhance the network size as well as the security level in comparison to the existing techniques. The technique ensures the k-connectivity among the nodes with a redundant method to provide backup for failed nodes. In the simulation section, the performance of the proposed scheme is evaluated using NS-2 based upon the real model MICAz. A discussion based on various obtained results is also given in the paper.

Event Based Data Gathering in Wireless Sensor Networks

2012 ◽  
pp. 445-462 ◽  
Author(s):  
Asfandyar Khan ◽  
Azween Abdullah ◽  
Nurul Hasan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Network Lifetime ◽  
Energy Savings ◽  
Detection System ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Detection Model ◽  
Physical Environments ◽  
Event Based

Wireless sensor networks (WSANs) are increasingly being used and deployed to monitor the surrounding physical environments and detect events of interest. In wireless sensor networks, energy is one of the primary issues and requires the conservation of energy of the sensor nodes, so that network lifetime can be maximized. It is not recommended as a way to transmit or store all data of the sensor nodes for analysis to the end user. The purpose of this “Event Based Detection” Model is to simulate the results in terms of energy savings during field activities like a fire detection system in a remote area or habitat monitoring, and it is also used in security concerned issues. The model is designed to detect events (when occurring) of significant changes and save the data for further processing and transmission. In this way, the amount of transmitted data is reduced, and the network lifetime is increased. The main goal of this model is to meet the needs of critical condition monitoring applications and increase the network lifetime by saving more energy. This is useful where the size of the network increases. Matlab software is used for simulation.

scholarly journals Node clone detection using a stable overlay network

2020 ◽  
Vol 10 (1) ◽  
pp. 316
Author(s):  
Balika J. Chelliah ◽  
M. S. Antony Vigil ◽  
M. S. Bennet Praba
Keyword(s):  
Wireless Sensor Networks ◽  
Overlay Networks ◽  
Overlay Network ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Level ◽  
Clone Detection ◽  
Data Prediction ◽  
High Security Level ◽  
Balanced Network

Wireless sensor networks consist of number of sensor nodes widely distributed in particular region to communicate and sharing the environmental information and also these data’s are stored in central location for further data prediction. Such nodes are susceptible to cloning attack where the adversary captures a node, replicates with the same identity as that of the captured node and deploys the clone back into the network, causing severe harm to the network. Hence to thwart such attacks, a distributed detection protocol is used with initiator-observer-inspector roles assigned randomly for the nodes to witness the clone and thereby broadcast the evidence through a balanced overlay network. Use of such balanced network provides high security level and reduces the communication cost when compared to other overlay networks with a reasonably less storage consumption.

Secure Deployment with Optimal Connectivity in Wireless Sensor Networks

2016 ◽  
Vol 7 (2) ◽  
pp. 1-21
Author(s):  
Anju Sangwan ◽  
Rishipal Singh
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Network Size ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Level ◽  
Real Model ◽  
Homogeneous Network ◽  
Basic Issue

In the hostile areas, deployment of the sensor nodes in wireless sensor networks is one of the basic issue to be addressed. The node deployment method has great impact on the performance metrics like connectivity, security and resilience. In this paper, a technique based on strong keying mechanism is proposed which will enhance the security of a non-homogeneous network using the random deployment of the nodes. For this, the q-composite key pre-distribution technique is presented with new flavor that will enhance the network size as well as the security level in comparison to the existing techniques. The technique ensures the k-connectivity among the nodes with a redundant method to provide backup for failed nodes. In the simulation section, the performance of the proposed scheme is evaluated using NS-2 based upon the real model MICAz. A discussion based on various obtained results is also given in the paper.

scholarly journals On the Use of Graphs for Node Connectivity in Wireless Sensor Networks for Hostile Environments

2019 ◽  
Vol 2019 ◽  
pp. 1-22
Author(s):  
Emmanuel García-González ◽  
Juan C. Chimal-Eguía ◽  
Mario E. Rivero-Angeles ◽  
Vicent Pla
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Data Gathering ◽  
Packet Delay ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Buffer Size ◽  
Distributed Data ◽  
Node Connectivity ◽  
Hostile Environments

Wireless sensor networks (WSNs) have been extensively studied in the literature. However, in hostile environments where node connectivity is severely compromised, the system performance can be greatly affected. In this work, we consider such a hostile environment where sensor nodes cannot directly communicate to some neighboring nodes. Building on this, we propose a distributed data gathering scheme where data packets are stored in different nodes throughout the network instead to considering a single sink node. As such, if nodes are destroyed or damaged, some information can still be retrieved. To evaluate the performance of the system, we consider the properties of different graphs that describe the connections among nodes. It is shown that the degree distribution of the graph has an important impact on the performance of the system. A teletraffic analysis is developed to study the average buffer size and average packet delay. To this end, we propose a reference node approach, which entails an approximation for the mathematical modeling of these networks that effectively simplifies the analysis and approximates the overall performance of the system.

Introducing Machine Learning to Wireless Sensor Networks

2020 ◽  
pp. 1-22
Author(s):  
Vidit Gulyani ◽  
Tushar Dhiman ◽  
Bharat Bhushan
Keyword(s):  
Machine Learning ◽  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
20Th Century ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Clustering Techniques ◽  
Reduce Power Consumption ◽  
Overall Performance ◽  
Hostile Environments

From its advent in mid-20th century, machine learning constantly improves the user experience of existing systems. It can be used in almost every field such as weather, sports, business, IoT, medical care, etc. Wireless sensor networks are often placed in hostile environments to observe change in surroundings. Since these communicate wirelessly, many problems such as localisation of nodes, security of data being routed create barriers for proper functioning of system. Extending the horizon of machine learning to WSN creates wonders and adds credibility to the system. This chapter aids to present various machine learning aspects applied on wireless sensor networks and the benefits and drawbacks of applying machine learning to WSN. It also describes various data aggregation and clustering techniques that aim to reduce power consumption and ensure confidentiality, authentication, integrity, and availability amongst sensor nodes. This could contribute to design and alter pre-existing ML algorithms to improve overall performance of wireless sensor networks.

scholarly journals Adaptable Security in Wireless Sensor Networks by Using Reconfigurable ECC Hardware Coprocessors

2010 ◽  
Vol 6 (1) ◽  
pp. 740823 ◽  
Author(s):  
J. Portilla ◽  
A. Otero ◽  
E. de la Torre ◽  
T. Riesgo ◽  
O. Stecklina ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Low Power ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Security Level ◽  
Radio Communications ◽  
Security Challenges ◽  
Field Programmable ◽  
Hardware Reconfiguration

Specific features of Wireless Sensor Networks (WSNs) like the open accessibility to nodes, or the easy observability of radio communications, lead to severe security challenges. The application of traditional security schemes on sensor nodes is limited due to the restricted computation capability, low-power availability, and the inherent low data rate. In order to avoid dependencies on a compromised level of security, a WSN node with a microcontroller and a Field Programmable Gate Array (FPGA) is used along this work to implement a state-of-the art solution based on ECC (Elliptic Curve Cryptography). In this paper it is described how the reconfiguration possibilities of the system can be used to adapt ECC parameters in order to increase or reduce the security level depending on the application scenario or the energy budget. Two setups have been created to compare the software- and hardware-supported approaches. According to the results, the FPGA-based ECC implementation requires three orders of magnitude less energy, compared with a low power microcontroller implementation, even considering the power consumption overhead introduced by the hardware reconfiguration.

scholarly journals Wireless Sensor Networks with Energy Efficient Organization

2002 ◽  
Vol 03 (03n04) ◽  
pp. 213-229 ◽  
Author(s):  
Mihaela Cardei ◽  
David MacCallum ◽  
Maggie Xiaoyan Cheng ◽  
Manki Min ◽  
Xiaohua Jia ◽  
...  
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Energy Savings ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sleep Mode ◽  
Target Area ◽  
Dominating Sets ◽  
Active Set ◽  
Sensor Applications

A critical aspect of applications with wireless sensor networks is network lifetime. Battery-powered sensors are usable as long as they can communicate captured data to a processing node. Sensing and communications consume energy, therefore judicious power management and scheduling can effectively extend the operational time. One important class of wireless sensor applications of deployment of large number of sensors in an area for environmental monitoring. The data collected by the sensors is sent to a central node for processing. In this paper we propose an efficient method to achieve energy savings by organizing the sensor nodes into a maximum number of disjoint dominating sets (DDS) which are activated successively. Only the sensors from the active set are responsible for monitoring the target area and for disseminating the collected data. All other nodes are into a sleep mode, characterized by a low energy consumption. We define the maximum disjoint dominating sets problem and we design a heuristic that computes the sets. Theoretical analysis and performance evaluation results are presented to verify our approach.

Localization Security in Wireless Sensor Networks

2008 ◽  
pp. 617-627 ◽  
Author(s):  
Yawen Wei ◽  
Zhen Yu ◽  
Yong Guan
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Location Information ◽  
Malicious Attacks ◽  
Distance Measurements ◽  
Secure Localization ◽  
Comprehensive Survey ◽  
Hostile Environments

Localization of sensor nodes is very important for many applications proposed for wireless sensor networks (WSN), such as environment monitoring, geographical routing, and target tracking. Because sensor networks may be deployed in hostile environments, localization approaches can be compromised by many malicious attacks. The adversaries can broadcast corrupted location information; they can jam or modify the transmitting signals between sensors to mislead them to obtain incorrect distance measurements or nonexistent connectivity links. All these malicious attacks will cause sensors not able to or wrongly estimate their locations. In this chapter, we summarize the threat models and provide a comprehensive survey and taxonomy of existing secure localization and verification schemes for wireless sensor networks.

scholarly journals Continuous Monitoring in Wireless Sensor Networks: A Fuzzy-Probabilistic Approach

2019 ◽  
Author(s):  
Flávio Nunes ◽  
José Maia
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Sensor Node ◽  
Energy Savings ◽  
Linear Prediction ◽  
Fuzzy Inference ◽  
Probabilistic Approach ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Sensor Field

This work presents and evaluates a fuzzy-probabilistic strategy to save energy in Wireless Sensor Networks (WSNs). The energy savings are obtained with the sensor nodes, no longer sensing and transmitting measurements. In this simple strategy, in each epoch each sensor node transmits its measurement with probability p, and does not transmit with probability (1 􀀀 p), does not correlate with that of any other sensor node. The task at the sink node, which is to estimate the sensor field at non-sensed points, is solved using fuzzy inference to impute the non-transmitted data followed by regression or interpolation of the sensed scalar field. In this, Nadaraya-Watson regression, regression with Fuzzy Inference and Radial Base Functions Interpolation are compared. The compromise curve between the value of p and the accuracy of the sensor field estimation measured by root mean square error (RMSE) is investigated. When compared to a published linear prediction strategy of the literature, the results show a small loss of performance versus the great simplification of the procedure in the sensor node, making it advantageous in applications that require extremely simple network nodes.

Sign in / Sign up

Export Citation Format

Share Document