Qualification: 
BE
s_lakshmi@blr.amrita.edu

Santhana Lakshmi S. currently serves as Sr.Lecturer at department of Computer Science,Amrita School of Engineering.She is currently pursuing her Ph.D.

Publications

Publication Type: Conference Paper

Year of Publication Publication Type Title

2017

Conference Paper

B. Sholaganga, Lakshmi P., and S .Santhanalakshmi, “Home Automation in Client-Server approach with user notification along with efficient security Alert System”, in International Conference On Smart Technologies For Smart Nation (SmartTechCon2017), Reva University, Bengaluru, 2017.

2017

Conference Paper

P. Deshpande, S .Santhanalakshmi, and Lakshmi P., “Experimental study of DiffieHellmam Key Exchange Algorithm on Embedded Devices”, in International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS 2017) , Chennai, 2017.

2015

Conference Paper

S .Santhanalakshmi, Dr. K. Sangeeta Iyer, and Patra, G. K., “Design and Analysis of Cryptographic Protocols using Computational Intelligence Techniques”, in International Conference on Inter-Research-Institute Student Seminar (IRISS 2015) , ACM India Annual Event at BITS, Goa, 2015.

2012

Conference Paper

S .Santhanalakshmi, Sudarshan, T. S. B., and Patra, G. K., “Neural Synchronization by Mutual Learning Using Genetic Approach for Secure Key Generation”, in International Conference on Security in Computer Networks Distributed Systems (SNDS-2012), IITM-K Techno park at Trivandrum, 2012, vol. 335, pp. 422-431.[Abstract]


Neural cryptography is a new way to create shared secret key. It is based on synchronization of Tree Parity Machines (TPM) by mutual learning. Two neural networks trained on their mutual output bits synchronize to a state with identical time dependent weights. This has been used for creation of a secure cryptographic secret key using a public channel. In this paper a genetic approach has been used in the field of neural cryptography for synchronizing tree parity machines by mutual learning process. Here a best fit weight vector is found using a genetic algorithm and then the training process is done for the feed forward network. The proposed approach improves the process of synchronization.

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Publication Type: Journal Article

Year of Publication Publication Type Title

2014

Journal Article

S .Santhanalakshmi, Dr. K. Sangeeta Iyer, and Patra, G. K., “Secure Key Stream Generation using Computational Intelligence Techniques”, Int. Journal Computer Technology & Applications, Month and Year of Publication, , vol. 5, pp. 967-972, 2014.

2014

Journal Article

S. D. Shenoy, Sharma, V., and S .Santhanalakshmi, “Automation of Timetable Generation using Genetic Algorithm”, Int.J.Computer Technology & Applications, vol. 5, pp. 1491-1494, 2014.[Abstract]


Finding a feasible lecture/tutorial timetable in a large university department is a challenging problem faced continually in educational establishments. This paper
presents an evolutionary algorithm (EA) based approach to solving a heavily constrained university timetabling problem. The approach uses a problem-specific chromosome representation. Heuristics and context-based reasoning have been used for obtaining feasible timetables in a reasonable computing time. An intelligent adaptive mutation scheme has been employed for speeding up the convergence. The comprehensive course timetabling system presented in this paper has been validated, tested and discussed using real world data from a large university.

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Faculty Research Interest: 
207
PROGRAMS
OFFERED
5
AMRITA
CAMPUSES
15
CONSTITUENT
SCHOOLS
A
GRADE BY
NAAC, MHRD
8th
RANK(INDIA):
NIRF 2018
150+
INTERNATIONAL
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