International Journal of Computer Network and Information Security (IJCNIS)
IJCNIS Vol. 10, No. 8, 8 Aug. 2018
Cover page and Table of Contents: PDF (size: 578KB)
Internet of Things for the Prevention of Black Hole Using Fingerprint Authentication and Genetic Algorithm Optimization
Full Text (PDF, 578KB), PP.17-26
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Author(s)
PoojaChandel
1,*
Rakesh Kumar
1
Index Terms
Internet of Things, Black Hole, Genetic algorithm, Fingerprint authentication, Ad Hoc Network
Abstract
The Internet is a communication network where two or more than two users communicate and exchange the data. Black hole attack is a security threat in which a malicious node drops some or all of the packets. The proposed framework implements a biometric authentication system into the communication network to verify the user and to save the user from any internal or external threat. The main objective is to integrate the biometric security with the communication network. The attack is supposed to be a Black hole which has been considered as a smart attack. Feature extraction of Fingerprint dataset will be done using minutiae extractor. This will extract ridge endings and ridge bifurcation from the thinned image. Genetic algorithm is usedto reduce the features to useful pool. If the user is authentic only then prevention mechanism against black hole is applied. Genetic Algorithm is used to find out black hole node based on the fitness function. Proposed model’s performance is evaluated using various metrics like delay, throughput, energy consumption and packet delivery ratio.
Cite This Paper
PoojaChandel, Rakesh Kumar, "Internet of Things for the Prevention of Black Hole Using Fingerprint Authentication and Genetic Algorithm Optimization", International Journal of Computer Network and Information Security(IJCNIS), Vol.10, No.8, pp.17-26, 2018. DOI:10.5815/ijcnis.2018.08.02
Reference
[1]Zeinab Kamal Aldein Mohammed, Elmustafa Sayed Ali Ahmed, “Internet of things applications, challenges and related future technologies”, World Scientific News, pp. 126-148, 2017.
[2]Suchitra, Vandana, “Internet of things and security issues”, International Journal of Computer Science and Mobile Computing, Vol. 5, Issue. 1, pp. 133-139, Jan. 2016.
[3]C. K. Nagpal, Chirag Kumar, Bharat Bhushan, Shailender
Gupta, "A study of black hole attack on MANET performance", IJMECS, vol.4, no.8, pp.47-53, 2012.
[4]Kumar Roshan,Vimal Bibhu,"Preventive aspect of black hole attack in mobile AD HOC network", IJCNIS, vol.4, no.6, pp.49-55, 2012.
[5]Aditi Roy, Nasir Memon, Arun Ross, “Masterprint: exploring the vulnerability of partial fingerprint-based authentication systems”, IEEE Transactions on Information Forensics and Security, Vol. 12, Issue. 9, pp. 2013-2025, Sept. 2017.
[6]Manisha Redhu and Balkishan, “Fingerprint recognition using minutiae extractar”, International Journal of Engineering Research and Applications (IJERA), Vol. 3, Issue 4, pp. 2488-2497, August 2013.
[7]Samayita Bhattacharya, Kalyani Mali, “Fingerprint recognition by classification using neural network and matching using minutiae (fingerprint recognition by NNMM Method)”, International Journal of Emerging Research in Management &Technology, Vol. 3, Issue 8, pp. 1-10, Aug. 2014.
[8]Ruud M. Bolle, Nalini K. Ratha and Sharath Pankanti, “Fingerprint minutiae: a constructive definition”, Springer International Workshop on Biometric Authentication, pp. 58-66, 2002.
[9]Richa Garg, Saurabh mittal, “Optimization by genetic algorithm”, International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, pp. 587-589, April 2014.
[10]Andras Rozsa, Albert E. Glock, Jr, Terrance E. Boult, “Genetic algorithm attack on minutiae-based fingerprint authentication and protected template fingerprint systems”, IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 100-108, 2015.
[11]K. F. Man, K. S. Tang, and S. Kwong, “Genetic algorithms: concepts and applications”, IEEE Transactions on Industrial Electronics, Vol. 43, No. 5, pp. 519-534, Oct. 1996.
[12]Pushpendra Kumar Yadav, Dr. N. L. Prajapati, “An overview of genetic algorithm and modeling”, International Journal of Scientific and Research Publications, Vol. 2, Issue 9, pp. 1-4, Sept. 2012.
[13]Meenakshi Moza, Suresh Kumar, "Improving the performance of routing protocol using genetic algorithm", International Journal of Computer Network and Information Security(IJCNIS), Vol.8, No.7, pp.10- 16, 2016.DOI: 10.5815/ijcnis.2016.07.02.
[14]Mouad. M. H. Ali, Vivek H. Mahale, PravinYannawar and A.T. Gaikwad, “Fingerprint recognition for person identification and verification based on minutiae matching”, 6th IEEE International Conference on Advanced Computing (IACC), pp. 332-339, 2016.
[15]Bikramjeet Singh, Dasari Srikanth, and C.R. Suthikshn Kumar, “Mitigating Effects of Black Hole Attack in Mobile Ad-Hoc Networks: Military Perspective”, 2nd IEEE International Conference on Engineering and Technology (ICETECH), March 2016.
[16]Ashish Kumar Jain and VrindaTokekar, “ Mitigating the effects of black hole attacks on AODV routing protocol in mobile ad hoc networks”, IEEE International Conference on Pervasive Computing(ICPC), pp.1-6, 2015.
[17]M. Rajesh Babu, S. Moses Dian, Siva Chelladurai and Mathiyalagan Palaniappan, “Proactive Alleviation Procedure to Handle Black Hole Attack and ItsVersion”, The Scientific World Journal, Vol. 2015, pp. 1-12, 2015.
[18]Arshdeep Kaur, Mandeep Kaur, “Prevention of black hole attack in manet using genetic algorithm”, International Journal of Advance Research in Science and Engineering, Vol. 4, pp. 153-163, May 2015.
[19]Chandeep Singh, Vishal Walia, Rahul Malhotra, “Genetic Optimization based Adaptive Approach for the Determination of Black Hole Attack in AODV Protocol”, 2nd International Conference on Science, Technology and Management, pp. 2742-2753, 2015.
[20]Rakesh Ranjan, Nirnemesh Kumar Singh, “Security Issues of Black Hole Attacks in MANET “, IEEE International Conference on Computing, Communication and Automation (ICCCA), pp. 452-457, 2015.
[21]Purneet Kaur, Jaspreet Kaur, “Finger print Recognition Using Genetic Algorithm and Neural Network”, International Journal of Computational Engineering Research, Vol. 3, pp. 41-46, 2013.