Call For Paper Volume:7 Issue:9 Sep'2020 |

Estimation Based Framework for Identifying Malicious Data Injections in Wireless Sensor Networks

Publication Date : 11/11/2016


DOI : 10.21884/IJMTER.2016.3115.MPSX2

Author(s) :

Sailaja Gokavarapu , Md. Abdul Azeem, Associate Professor.


Volume/Issue :
Volume 3
,
Issue 10
(11 - 2016)



Abstract :

—Wireless Sensor Networks are widely advocated to monitor environmental parameters, structural integrity of the built environment and use of urban spaces, services and utilities. However, embedded sensors are vulnerable to compromise by external actors through malware but also through their wireless and physical interfaces. Compromised sensors can be made to report false measurements with the aim to produce inappropriate and potentially dangerous responses. Such malicious data injections can be particularly difficult to detect if multiple sensors have been compromised as they could emulate plausible sensor behaviour such as failures or detection of events where none occur. A novel algorithm is proposed to identify malicious data injections and build measurement estimates that are resistant to several compromised sensors even when they collude in the attack. A methodology is also proposed to apply this algorithm in different application contexts and evaluate its results. The algorithm consists of three phases viz., Estimation, similarity check and characterization. In similarity check, there are two tests that capture the characteristics of most event detection criteria. The magnitude test verifies that reported measurements are close in magnitude to their estimates. The shape test verifies that the estimate and reported signal have a similar shape. This work only concentrated on the detection of malicious data injections, the entire process is centralized and is being carried out at the base station, which has further been enhanced to distributed architecture. As it is an in-network process, the process of detection of malicious injections is evenly distributed in the network. In order to avoid transmission of malicious data through the network nodes and to curtail the energy wastage in network, the detection is done at the cluster head level itself by maintaining the accuracy using the LEACH characteristic.


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Estimation Based Framework for Identifying Malicious Data Injections in Wireless Sensor Networks

October 27, 2016