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Data Passing with High Security through Non Infected Nodes in Networks

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Data Passing with High Security through Non Infected Nodes in Networks


K. Malarvizhi | Prof. P. Parthasarathy | Dr. S. Shankar



K. Malarvizhi | Prof. P. Parthasarathy | Dr. S. Shankar "Data Passing with High Security through Non Infected Nodes in Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-6, October 2019, pp.1274-1278, URL: https://www.ijtsrd.com/papers/ijtsrd29387.pdf

Path-based network diffusion kernel is its tenability, that it can consider different number of shortest paths in kernel computation. This resembles, vaguely, a Taylor-expansion of network topology to form a diffusion kernel with different orders of expansion. One can extend this key idea to design other network diffusion kernels to approximate other general diffusion models such as SIR the challenge of determining sources is compounded as the true propagation dynamics are typically unknown, and when they have been directly measured, they rarely conform to the assumptions of any of the well-studied models. In this paper introduce a method called Network Infusion (NI) that has been designed to circumvent these issues, making source inference practical for large, complex real world networks. A stateless receiver-based multicast (RBMulticast) protocol that simply uses a list of the multicast members’ (e.g., sinks’) addresses, embedded in packet headers, to enable receivers to decide the best way to forward the multicast traffic. This protocol, called Receiver-Based Multicast, exploits the knowledge of the geographic locations of the nodes to remove the need for costly state maintenance. The key idea is that to infer the source node in the network, full characterization of diffusion dynamics, in many cases, may not be necessary. This objective is achieved by creating a diffusion kernel that well-approximates standard diffusion models such as the susceptible-infected diffusion model, but lends itself to inversion, by design, via likelihood maximization or error minimization. We apply NI for both single-source and multi-source diffusion, for both single-snapshot and multi-snapshot observations, and for both homogeneous and heterogeneous diffusion setups. We prove the mean-field optimality of NI for different scenarios, and demonstrate its effectiveness over several synthetic networks. Moreover, we apply NI to a real-data application, identifying news sources in the Digg social network, and demonstrate the effectiveness of NI compared to existing methods.

Network Infusion, susceptible-infected, EGMP


IJTSRD29387
Volume-3 | Issue-6, October 2019
1274-1278
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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