scholarly journals Energy Optimization on Symmetric Key Encryption and Decryption Algorithm using Genetic Algorithm

2019 ◽  
Vol 8 (10) ◽  
pp. 1280-1291
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Power Consumption ◽  
Random Number ◽  
Energy Optimization ◽  
Pseudo Random Number ◽  
Encryption And Decryption ◽  
Ascii Code ◽  
Symmetric Key

In this paper we have proposed energy optimization on symmetric key encryption and decryption algorithm are using genetic algorithm where we have used symmetric key for encryption & decryption algorithm that optimize the energy in terms of power consumption related to the laptop battery. This method combines the concept of a genetic algorithms and cryptography in very different ways. The algorithm uses deterministic way to generate pseudo random number and applied crossover & mutation deterministically. The algorithm exploits the features of the GA deterministically because GA is fast. Finally we got the actual message of ASCII code by using decrypted algorithms minimises power consumption relatively

scholarly journals Genetic Algorithm in Hill Cipher Encryption

2017 ◽  
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Evaluation Function ◽  
Hill Cipher ◽  
Encryption And Decryption ◽  
The Matrix ◽  
The Hill

The matrix in Hill Cipher was designed to perform encryption and decryption. Every column and row must be inserted by integer numbers. But, not any key that can be given to the matrix used for the process. The wrong determinant result cannot be used in the process because it produces the incorrect plaintext when doing the decryption after the encryption. Genetic algorithms offer the optimized way to determine the key used for encryption and decryption on the Hill Cipher. By determining the evaluation function in the genetic algorithm, the key that fits the composition will be obtained. By implementing this algorithm, the search of the key on the Hill Cipher will be easily done without spending too much time. Genetic algorithms do well if it is combined with Hill Cipher.

scholarly journals Encryption and Decryption of a Message Involving Genetic Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 3920-3923
Keyword(s):  
Genetic Algorithm ◽  
Encryption And Decryption ◽  
Symmetric Key ◽  
Crossover And Mutation

The aim of this paper is to establish an algorithm for encryption and decryption of a message based on symmetric key cryptosystem involving Genetic Algorithm. In the proposed algorithm we use substitution algorithm, genetic crossover and mutation technique.

Genetic Algorithm-Based Pseudo Random Number Generation for Cloud Security

2022 ◽  
pp. 209-236
Author(s):  
Sudeepa Keregadde Balakrishna ◽  
Sannidhan Manjaya Shetty ◽  
Jason Elroy Martis ◽  
Balasubramani Ramasamy
Keyword(s):  
Genetic Algorithm ◽  
Random Number ◽  
Random Number Generation ◽  
Cloud Security ◽  
Number Generation ◽  
Pseudo Random Number

An Efficient Image Encryption Using Merkle-Hellman, Elgamal and Genetic Algorithm for Color Images

2015 ◽  
Vol 719-720 ◽  
pp. 1140-1147 ◽  
Author(s):  
G. Lokeshwari ◽  
S. Udaya Kumar ◽  
Sree Vidya Susarla
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Block Size ◽  
Data Encryption ◽  
Color Images ◽  
Multimedia Systems ◽  
Digital Data ◽  
Original Image ◽  
Encryption And Decryption

The proliferation of digitized media due to rapid growth of network multimedia systems has created an urgent need for information security due to the ever increasing unauthorized manipulation and reproduction of original digital data. In this paper an approach based on Merkle-Hellman, ElGamal and Genetic algorithms is proposed for data encryption and decryption. The strength of the cipher is increased further by using genetic algorithm. Experimental results show that the proposed approach can be implemented on images of any size which retain the quality of the image while retrieving the original image. This aspect helps in providing the reduction in block size without compromise in the quality of the image and security as well.

RECONFIGURABLE LOW POWER ARCHITECTURE FOR FAULT TOLERANT PSEUDO-RANDOM NUMBER GENERATION

2014 ◽  
Vol 23 (01) ◽  
pp. 1450002 ◽  
Author(s):  
NEMANJA SAVIĆ ◽  
MILE STOJČEV ◽  
TATJANA NIKOLIĆ ◽  
VLADIMIR PETROVIĆ ◽  
GORAN JOVANOVIĆ
Keyword(s):  
Power Consumption ◽  
Low Power ◽  
High Speed ◽  
Random Number ◽  
Fault Tolerant ◽  
Design Solution ◽  
Ip Core ◽  
Fpga Architecture ◽  
Pseudo Random Number ◽  
Bicmos Technology

High operating speed, fault tolerance (FT), low power and reconfiguration become today dominant issues during development and design of linear feedback shift registers (LFSRs), used as sequence generators, with randomness properties, in a process of testing complex CMOS VLSI ICs. In our design solution, we accomplish FT by using triple modular redundancy (TMR), i.e., a hardware scheme that uses spatial redundancy. For reduction of dynamic power consumption, clock-gating technique, as a simple and effective method, is implemented. The reconfigurable FPGA architecture provides us a feature to program and configure the degree of the primitive polynomial that the LFSR uses. High speed of operation, over 100 MHz, during testing is achieved by using circuits fabricated in submicron technology. An architecture which integrates in a single structure (IP core) all aforementioned design issues, named fault tolerant reconfigurable low-power pseudo-random number generator (FT_RLRG), is described in this article. The design of FT_RLRG is of practical interest in testing triple modular FT systems in the presence of single event upsets (SEUs), especially in a case when the design is SRAM-based. As an IP core the FT_RLRG has been implemented both on FPGA and ASIC technology. The main idea was to design a low-cost and low-power hardware structure which is able to adjust to any standards (past, present and future) operating at high-speed with different polynomials (currently up to 32nd order). The performance of FT_RLRG in respect to speed of operation (up to 150 MHz for FPGA and ASIC designs), low hardware overhead (0.033 mm2 area for ASIC and up to 530 slices for FPGA) and low-power consumption (0.45 mW for ASIC), for three different FPGA architecture (Spartan-3E, Virtex-4 and Virtex-6LP) and as an ASIC design implemented in 130 nm SiGe BiCMOS technology, have been estimated.

scholarly journals Dynamic Key Matrix of Hill Cipher Using Genetic Algorithm

2017 ◽  
Vol 6 (4) ◽  
pp. 313
Author(s):  
Andysah Putera Utama Siahaan
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Evaluation Function ◽  
Hill Cipher ◽  
Encryption And Decryption ◽  
The Matrix ◽  
Dynamic Key ◽  
The Hill

The matrix in Hill Cipher was designed to perform encryption and decryption. Every column and row must be inserted by integer numbers. But, not any key that can be given to the matrix used for the process. The wrong determinant result cannot be used in the process because it produces the incorrect plaintext when doing the decryption after the encryption. Genetic algorithms offer the optimized way to determine the key used for encryption and decryption on the Hill Cipher. By determining the evaluation function in the genetic algorithm, the key that fits the composition will be obtained. By implementing this algorithm, the search of the key on the Hill Cipher will be easily done without spending too much time. Genetic algorithms do well if it is combined with Hill Cipher.

scholarly journals Cryptography Involving Musical Notes and Genetic Algorithm

2019 ◽  
Vol 9 (2) ◽  
pp. 2563-2565
Keyword(s):  
Genetic Algorithm ◽  
Encryption And Decryption ◽  
Symmetric Key

The object of this paper is to established a symmetric key algorithm for encryption and decryption of a message involving musical notes (India and Western) and genetic algorithm. This algorithm does not only encrypt the message but it also reduces the chance of deciphering from hackers.

Formulation of Colors Using a Genetic Algorithm

2012 ◽  
Vol 17 (4) ◽  
pp. 241-244
Author(s):  
Cezary Draus ◽  
Grzegorz Nowak ◽  
Maciej Nowak ◽  
Marcin Tokarski
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Production Process ◽  
Computer Technology ◽  
Manual Method ◽  
Apply Genetic ◽  
Computer Aided ◽  
Multiple Samples ◽  
Plastics Industry

Abstract The possibility to obtain a desired color of the product and to ensure its repeatability in the production process is highly desired in many industries such as printing, automobile, dyeing, textile, cosmetics or plastics industry. So far, most companies have traditionally used the "manual" method, relying on intuition and experience of a colorist. However, the manual preparation of multiple samples and their correction can be very time consuming and expensive. The computer technology has allowed the development of software to support the process of matching colors. Nowadays, formulation of colors is done with appropriate equipment (colorimeters, spectrophotometers, computers) and dedicated software. Computer-aided formulation is much faster and cheaper than manual formulation, because fewer corrective iterations have to be carried out, to achieve the desired result. Moreover, the colors are analyzed with regard to the metamerism, and the best recipe can be chosen, according to the specific criteria (price, quantity, availability). Optimaization problem of color formulation can be solved in many diferent ways. Authors decided to apply genetic algorithms in this domain.

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