506 research outputs found
GTRSSN: Gaussian trust and reputation system for sensor networks
This paper introduces a new Gaussian trust and reputation system for wireless sensor networks based on sensed continuous events to address security issues and to deal with malicious and unreliable nodes. It is representing a new approach of calculating trust between sensor nodes based on their sensed data and the reported data from surrounding nodes. It is addressing the trust issue from a continuous sensed data which is different from all other approaches which address the issue from communications and binary point of view. © Springer Science+Business Media B.V. 2008
Bayesian fusion algorithm for inferring trust in wireless sensor networks
This paper introduces a new Bayesian fusion algorithm to combine more than one trust component (data trust and communication trust) to infer the overall trust between nodes. This research work proposes that one trust component is not enough when deciding on whether or not to trust a specific node in a wireless sensor network. This paper discusses and analyses the results from the communication trust component (binary) and the data trust component (continuous) and proves that either component by itself, can mislead the network and eventually cause a total breakdown of the network. As a result of this, new algorithms are needed to combine more than one trust component to infer the overall trust. The proposed algorithm is simple and generic as it allows trust components to be added and deleted easily. Simulation results demonstrate that a node is highly trustworthy provided that both trust components simultaneously confirm its trustworthiness and conversely, a node is highly untrustworthy if its untrustworthiness is asserted by both components. © 2010 ACADEMY PUBLISHER
Modelling Trust In Wireless Sensor Networks from the Sensor Reliability Prospective
This paper surveys the state of the art trust-based systems in Wireless Sensor Networks (WSN); it highlights the difference between Mobile ad hoc networks (MANET) and WSN and based on this observed difference (monitoring events and reporting data) a new trust model is introduced, which takes sensor reliability as a component of trust. A new definition of trust is created based on the newly introduced component of trust (sensor data) and an extension of node misbehaviour classification is also presented based on this new component of trust
The non-standard finite difference scheme for linear fractional PDEs in fluid mechanics
AbstractA non-standard finite difference scheme is developed to solve the linear partial differential equations with time- and space-fractional derivatives. The Grunwald–Letnikov method is used to approximate the fractional derivatives. Numerical illustrations that include the linear inhomogeneous time-fractional equation, linear space-fractional telegraph equation, linear inhomogeneous fractional Burgers equation and the fractional wave equation are investigated to show the pertinent features of the technique. Numerical results are presented graphically and reveal that the non-standard finite difference scheme is very effective and convenient for solving linear partial differential equations of fractional order
Can we trust trusted nodes in wireless sensor networks?
In this paper we extend our previously designed trust model in wireless sensor networks to include both; communication trust and data trust. Trust management in wireless sensor networks is predominantly based on routing messages; whether the communication has happened or not (successful and unsuccessful transactions). The uniqueness of sensing data in wireless sensor networks introduces new challenges in calculating trust between nodes (data trust). If the overall trust is based on just the communication trust, it might mislead the network, that is; untrustworthy nodes in terms of sensed data can be classified as trusted nodes due to their communication capabilities. Hence we need to develop new trust models to address the issue of the actual sensed data. Here we are comparing the two trust models and proving that one model by itself is not enough to decide on the trustworthiness of a node, so new techniques are required to combine both data trust and communication trust. ©2008 IEEE
RBATMWSN: Recursive Bayesian approach to trust management in wireless sensor networks
This paper introduces a new trust model and a reputation system for wireless sensor networks based on a sensed continuous data. It establishes the continuous version of the beta reputation system introduced in [1] and applied to binary events and presents a new Gaussian Reputation System for Sensor Networks (GRSSN) . We introduce a theoretically sound Bayesian probabilistic approach for mixing second-hand information from neighbouring nodes with directly observed information. ©2007 IEEE
Mobility of a One-Dimensional Confined File of Water Molecules as a Function of File Length.
Approximate analytic solution of fractional heat-like and wave-like equations with variable coefficients using the differential transforms method
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