A novel Approach to System Security using Derived Odor Keys with Weight Elimination Neural Algorithm (DOK-WENA)

Authors

  • Mahmoud Zaki Iskandarani Al-Zaytoonah University of Jordan

DOI:

https://doi.org/10.14738/tmlai.22.138

Keywords:

Genetic Algorithm, Olfactory, Odor Sensor, Software, Neural, Algorithm, Security.

Abstract

 A novel security technique for network and data communication applications that makes use of odors as password generators is developed and tested. The developed system employs odor keys derived from an original key together with the original key to allow access to systems and networks. The used key combinations are initially unknown to the user, and if detected while in the transmission process, there is no way of being able to be emulated.

The uniqueness of the developed system is that it is not necessary for an odor key to be an exact replica of the original, but to be derived from the original. This is a chemical encryption and encoding as the right key will not be detected by anyone since it is a derived version and not a match. Genetic Algorithm is used to emulate the chemical derivation and to make up for any margin of odor detection error and sensors tolerances.

Author Biography

Mahmoud Zaki Iskandarani, Al-Zaytoonah University of Jordan

B.Eng (Hons), MS.c (Neural Processors), Ph.D (Intelligent Techniques) from The University of Warwick-UK. Worked as Research Fellow at the Advanced Technology Centre at the University. I am  47 years old  British National but now works in Jordan.

 

Department of Computer Science, Faculty if Science and Information Technology. Professor Intelligent Systems & Sensors.

References

. E. Kim 1, S. Lee, J. Kim, C. Kim, Y. Tae Byun, H. Kim, T. Lee, Pattern Recognition for Selective Odor Detection with Gas Sensor Arrays. Sensors. 2012. 12(12): p.16262-16273. doi:10.3390/s121216262.

. Y. Tian, X. Kang, Y. Li, W. Li, A. Zhang, J. Yu, Y. Li, Identifying Rhodamine Dye Plume Sources in Near-Shore Oceanic Environments by Integration of Chemical and Visual Sensors, Sensors. 2013. 13(13): p.3776-3798. doi:10.3390/s130303776.

. T. Dymerski, J. Gębicki, P. Wiśniewska , M. Śliwińska, W. Wardencki, J. Namieśnik, Application of the Electronic Nose Technique to Differentiation between Model Mixtures with COPD Markers, Sensors. 2013. 13(4): p.5008-5027. doi:10.3390/s130405008.

. K. Fujioka, E. Arakawa, J. Kita, Y. Aoyama, Y. Manome, K. Ikeda, K. Yamamoto, Detection of Aeromonas hydrophila in Liquid Media by Volatile Production Similarity Patterns, Using a FF-2A Electronic Nose, Sensors. 2013. 13(1): p.736-745. doi:10.3390/s130100736.

. W. Yu, S. Wang, Key pre-distribution using combinatorial designs for wireless sensor networks, nodes have the same capabilities and constraints, WSEAS Transactions on Mathematics, 2013. 12(1): p.32-41. doi:10.1109/TNET.2007.892879.

. Y. Lan, X. Zheng, J. Westbrook, J. Lopez, R. Lacey, W. Hoffmann, Identification of Stink Bugs Using an Electronic Nose. Journal of Bionic Engineering, 2008. 5(1): p.172-180. doi:10.1016/S1672-6529(08)60090-6.

. M. Zarzo, Effect of Functional Group and Carbon Chain Length on the Odor Detection Threshold of Aliphatic Compounds, Sensors, 2012. 12(1): p.4105-4112. doi:10.3390/s120404105.

. P. Puligundla, J. Jung, S. Ko, Carbon dioxide sensors for intelligent food packaging applications, Food Control, 2012. 25(1): p.328-333. doi.org/10.1016/j.foodcont.2011.10.043.

. M. Mannoor, H. Tao, J. Clayton, A. Sengupta, D. Kaplan, R. Naik, N. Verma, F. Omenetto, M. McAlpine, Graphene-based wireless bacteria detection on tooth enamel. Nature Communications, 2012. 763(3): p.1-8. Doi:10.1038/ncomms1767.

. F. Benrekia, M. Attari, M. Bouhedda, Gas Sensors Characterization and Multi-layer Perceptron (MLP) Hardware Implementation for Gas Identification Using a Field Programmable Gate Array (FPGA), Sensors, 2013. 13(1): p.2967-2985, 2013 doi:10.3390/s130302967.

.B. Zhou, J. Wang, Detection of Insect Infestations in Paddy Field using an Electronic Nose, International Journal Of Agriculture & Biology, 2011. 13(5): p.708-712. doi:11–058/SAE/2011/13–5–707–712.

. C. Wongchoosuk, M. Lutz, T. Kerd-charoen, Detection and Classification of Human Body Odor Using an Electronic Nose, Sensors, 2009. 9(1): p. 7234-7249. doi:10.3390/s90907234.

.H. Lee, W.Yang, N. Choi, S. Moon, Encapsulation of Semiconductor Gas Sensors with Gas Barrier Films for USN Application, ETRI Journal, 2012. 34(5): p.713-718. doi:10.4218/etrij.12.0112.0266.

. A. Lotfi, S. Coradeschi, Odor Recognition for Intelligent Systems, IEEE intelligent Systems, 2008. 23(1): p.41-48. doi: 10.1109/MIS.2008.11.

. M. Ke, M. Lee, C. Lee, L. Fu, A MEMS-based Benzene Gas Sensor with a Self-heating WO3 Sensing Layer, Sensors, 2009. 9(4): p.2895-2906. doi:10.3390/s90402895.

. M. Iskandarani, Low Pass Filter Model for Chemical Sensors in Response to Gases and Odors, American Journal of Applied Sciences, 2012. 9(4): p.605-608. doi: 10.3844/ajassp.2012.605.608.

. M. Iskandarani, Inheritance based Intelligent Technique Employing Nested-XOR with Recursion for Recognition and Classification of Odors using Multi-Sensor Nose System, American Journal of Applied Sciences, 2011. 8(9): p.910-917. 10.3844/ajassp.2011.910.917.

. M. Iskandarani, A Novel Odor Key Technique for Security Applications Using Electronic Nose System, American Journal of Applied Sciences, 2010, 7(8): p.1118-1122. doi:10.3844/ajassp.2010.1118.1122.

. M. Iskandarani, A Novel Approach to Signal Detection of Sensor Array Units Using 5-3-1 Rule Based Matched Filter Algorithm with Intelligent Identifiers, American Journal of Engineering and Applied Sciences, 2010. 3(2): p.427-432. doi: 10.3844/ajeassp.2010.427.432.

. M. Iskandarani, Mathematical Modeling and Characterization of Thin Film, Narrow Gap Sensor Array Units (SAU), American Journal of Applied Sciences, 7(9): p.1277-1284. doi: 10.3844/ajassp.2010.1277.1284.

Downloads

Published

2014-04-11

How to Cite

Iskandarani, M. Z. (2014). A novel Approach to System Security using Derived Odor Keys with Weight Elimination Neural Algorithm (DOK-WENA). Transactions on Engineering and Computing Sciences, 2(2), 20–31. https://doi.org/10.14738/tmlai.22.138