Linguistic Schemes Encoding Text Message

Authors

  • K. Sarath Kannan  Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu, India
  • Dr. S. S. Dhenakaran  Department of Computer Science, Alagappa University, Karaikudi, Tamil Nadu, India

Keywords:

Encryption, Text Mixing, Linguistic Characters, Secret Message.

Abstract

Today websites and mobile applications are attacked by malicious, Ransom ware software designed to block information. It means sharing of websites and mobile apps information has low security. Cryptography is an art of providing security to messages before sharing them on insecure communication lines. The main aim of the paper is to propose a innovative encryption method adopting multilingualism approach where text message symbols are replaced by linguistic characters. An Unauthorized person cannot recognize the encrypted data while data transmission occurs. This method uses characters of four Indian languages Tamil, Hindi, Telugu, and Malayalam. This method encrypts plaintext and produces unintelligible linguistic codes. The outcome of encryption has a mixture of linguistic characters which cannot be understood by individual. Further, the initial experiments and results have shown a promising security level for proposed multilingualism technique. The proposed method is language-dependent approach providing new perspective with excellent potential for yielding secret codes.

References

  1. GanapathirajuM., BalakrishnanM., BalakrishnanN., and Reddy R., "Om: One tool for many (Indian) languages,"Journal of Zhejiang University Science, vol. 6A, no. 11,pp. 1348-1353,2005.
  2. R Seethalakshmi et.al., "Optical Character Recognition for Printed Tamil Text using Unicode", Journal of Zhejiang University Science, Vol. 6, No. 11, pp. 1297-1305, 2005.
  3. Arafat Awajan and Enas Abu Jrai, "Hybrid Techniques for Arabic Text Compression", Global Journal of Computer Science and Technology, Vol. 15, No. 1, pp. 23-27, 2015.
  4. B.Vijayalakshmi and N. Sasirekha," Lossless Text Compression For Unicode Tamil Documents" Department of Computer Science, Vidyasagar College of Arts and Science, India, Volume: 08, Issue: 02
  5. A. Bharath, S. Madhvanath , "Hidden Markov Models for Online Handwritten Tamil Word Recognition", 9th IEEE International Conference on Document Analysis and Recognition , 2007, Curitiba,Brazil, pp. 506-510.
  6. Md. Ahsanur Rahman, and Md. Abdus Sattar," A New Approach to Sort Unicode Bengali Text" 5th International Conference on Electrical and Computer Engineering ICECE 2008, 20-22 December 2008,
  7. SDivakaran, C.L. Biji, C.Anjali and Achuth Sankar S. Nair, "Malayalam Text Compression", International Journal of Information Systems and Engineering, Vol. 1, No. 1, pp. 7-11, 2013.
  8. Siva Jyothi Chandra, Ashlesha Pandhare and Mamatha Vani, "Multilingual Font Creation by Mapping Unicode to ASCII", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 9, pp. 12-18, 2015.
  9. Ajantha Devi and S.Santhosh Baboo, "Embedded Optical Character Recognition on Tamil Text Image using Raspberry Pi", International Journal of Computer Science Trends and Technology, Vol. 2, No. 4, pp. 11-15, 2014.
  10. Siva Jyothi Chandra, Ashlesha Pandhare and Mamatha Vani, "Multilingual Font Creation by Mapping Unicode to ASCII", International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 5, No. 9, pp. 12-18, 2015.

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Published

2018-06-30

Issue

Section

Research Articles

How to Cite

[1]
K. Sarath Kannan, Dr. S. S. Dhenakaran, " Linguistic Schemes Encoding Text Message, International Journal of Scientific Research in Science and Technology(IJSRST), Online ISSN : 2395-602X, Print ISSN : 2395-6011, Volume 4, Issue 8, pp.500-503, May-June-2018.