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Securing Vehicle Numbers using Artificial Neural Networks

E. Narwal1 , S. Gill2

  1. Department of Mathematics, Maharshi Dayanand University, Rohtak, India.
  2. Department of Mathematics, Maharshi Dayanand University, Rohtak, India.

Correspondence should be addressed to: ekta_narwal@yahoo.com.

Section:Research Paper, Product Type: Journal Paper
Volume-5 , Issue-10 , Page no. 195-199, Oct-2017

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v5i10.195199

Online published on Oct 30, 2017

Copyright © E. Narwal, S. Gill . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: E. Narwal, S. Gill, “Securing Vehicle Numbers using Artificial Neural Networks,” International Journal of Computer Sciences and Engineering, Vol.5, Issue.10, pp.195-199, 2017.

MLA Style Citation: E. Narwal, S. Gill "Securing Vehicle Numbers using Artificial Neural Networks." International Journal of Computer Sciences and Engineering 5.10 (2017): 195-199.

APA Style Citation: E. Narwal, S. Gill, (2017). Securing Vehicle Numbers using Artificial Neural Networks. International Journal of Computer Sciences and Engineering, 5(10), 195-199.

BibTex Style Citation:
@article{Narwal_2017,
author = {E. Narwal, S. Gill},
title = {Securing Vehicle Numbers using Artificial Neural Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {10 2017},
volume = {5},
Issue = {10},
month = {10},
year = {2017},
issn = {2347-2693},
pages = {195-199},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=1498},
doi = {https://doi.org/10.26438/ijcse/v5i10.195199}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v5i10.195199}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=1498
TI - Securing Vehicle Numbers using Artificial Neural Networks
T2 - International Journal of Computer Sciences and Engineering
AU - E. Narwal, S. Gill
PY - 2017
DA - 2017/10/30
PB - IJCSE, Indore, INDIA
SP - 195-199
IS - 10
VL - 5
SN - 2347-2693
ER -

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Abstract

In automatic gate entry system security of vehicle numbers stored in the computer system is a crucial issue because in some parking areas only few important vehicles are permitted. The numbers of permitted vehicles are stored in computer systems. Cryptography based security systems are used to secure these numbers, but in modern environment this type of secure data can also be hacked and altered by the unauthorized users. In order to solve these vulnerable problems, in this paper, we try to create a security mechanism by using Artificial Neural Network (ANN) to protect the data stored on a computer device against unauthorized access. In place of saving vehicle numbers in actual form or in form of alphanumeric data into a text file, we store them in the form of network parameters and these parameters are generated by the back propagation algorithm of ANN using neural network toolbox of MATLAB. This type of security approach is the newest form of cryptography and also cracking of these types of parameters is not possible till today.

Key-Words / Index Term

Artificial Neural Network; Back Propagation; Cryptography; Automatic Gate Entry System

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