A Scalable Grouping Random Key Predistribution Scheme for Large Scale Distributed Sensor Networks

Author(s):  
Po-Jen Chuang ◽  
Tun-Hao Chao ◽  
Bo-Yi Li
2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Jugminder Kaur ◽  
Sandeep S. Gill ◽  
Balwinder S. Dhaliwal

Security is always a major concern in wireless sensor networks (WSNs). Several trust based routing protocols are designed that play an important role in enhancing the performance of a wireless network. However they still have some disadvantages like limited energy resources, susceptibility to physical capture, and little protection against various attacks due to insecure wireless communication channels. This paper presents a secure trust based key management (STKF) routing framework that establishes a secure trustworthy route depending upon the present and past node to node interactions. This route is then updated by isolating the malicious or compromised nodes from the route, if any, and a dedicated link is created between every pair of nodes in the selected route with the help of “q” composite random key predistribution scheme (RKPS) to ensure data delivery from source to destination. The performance of trust aware secure routing framework (TSRF) is compared with the proposed routing scheme. The results indicate that STKF provides an effective mechanism for finding out a secure route with better trustworthiness than TSRF which avoids the data dropping, thereby increasing the data delivery ratio. Also the distance required to reach the destination in the proposed protocol is less hence effectively utilizing the resources.


Author(s):  
Torsten Licht ◽  
Abhijit Deshmukh

As sensor hardware becomes more sophisticated, smaller in size and increasingly affordable, use of large scale sensor networks is bound to become a reality in several application domains, such as vehicle condition monitoring, environmental sensing and security assessment. The ability to incorporate communication and decision capabilities in individual or groups of sensors, opens new opportunities for distributed sensor networks to monitor complex engineering systems. In such large scale sensor networks, the ability to integrate observations or inferences made by distributed sensors into a single hypothesis about the state of the system is critical. This paper addresses the sensor integration issue in hierarchically organized sensor networks. We propose a multi-agent architecture for distributed sensor networks. We present a new formalism to represent causal relations and prior beliefs of hierarchies of sensors, called Hierarchically Organized Bayesian Networks (HOBN), which is a semantic extension of Multiply Sectioned Bayesian Networks (MSBN). This formalism allows a sensor to reason about the integrity of a sensed signal or the integrity of neighboring sensors. Furthermore, we can also evaluate the consistency of local observations with respect to the knowledge of the system gathered up to that point.


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