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.

scholarly journals Strategic Team AI Path Plans: Probabilistic Pathfinding

2008 ◽  
Vol 2008 ◽  
pp. 1-6 ◽  
Author(s):  
Tng C. H. John ◽  
Edmond C. Prakash ◽  
Narendra S. Chaudhari
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Computer Games ◽  
Fitness Function ◽  
New Method ◽  
High Quality ◽  
Plan Generation ◽  
Novel Method ◽  
Games And Simulations

This paper proposes a novel method to generate strategic team AI pathfinding plans for computer games and simulations using probabilistic pathfinding. This method is inspired by genetic algorithms (Russell and Norvig, 2002), in that, a fitness function is used to test the quality of the path plans. The method generates high-quality path plans by eliminating the low-quality ones. The path plans are generated by probabilistic pathfinding, and the elimination is done by a fitness test of the path plans. This path plan generation method has the ability to generate variation or different high-quality paths, which is desired for games to increase replay values. This work is an extension of our earlier work on team AI: probabilistic pathfinding (John et al., 2006). We explore ways to combine probabilistic pathfinding and genetic algorithm to create a new method to generate strategic team AI pathfinding plans.

scholarly journals Utilizing Model Knowledge for Design Developed Genetic Algorithm to Solving Problem

2018 ◽  
Vol 3 (2) ◽  
pp. 172
Author(s):  
Hamidreza Salmani mojaveri
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Parallel Machines ◽  
Job Shop ◽  
Optimization Problems ◽  
Premature Convergence ◽  
Local Optimum ◽  
Scheduling Problems ◽  
Algorithm Implementation

One of the discussed topics in scheduling problems is Dynamic Flexible Job Shop with Parallel Machines (FDJSPM). Surveys show that this problem because of its concave and nonlinear nature usually has several local optimums. Some of the scheduling problems researchers think that genetic algorithms (GA) are appropriate approach to solve optimization problems of this kind. But researches show that one of the disadvantages of classical genetic algorithms is premature convergence and the probability of trap into the local optimum. Considering these facts, in present research, represented a developed genetic algorithm that its controlling parameters change during algorithm implementation and optimization process. This approach decreases the probability of premature convergence and trap into the local optimum. The several experiments were done show that the priority of proposed procedure of solving in field of the quality of obtained solution and convergence speed toward other present procedure.

Genetic Algorithms for Decision-Making in Cognitive Radio Networks

2013 ◽  
pp. 247-263
Author(s):  
Tommy Hult ◽  
Abbas Mohammed
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Cognitive Radio ◽  
Search Space ◽  
Radio Spectrum ◽  
Dynamic Decision Making ◽  
Optimal Point ◽  
Optimization Search

Efficient use of the available licensed radio spectrum is becoming increasingly difficult as the demand and usage of the radio spectrum increases. This usage of the spectrum is not uniform within the licensed band but concentrated in certain frequencies of the spectrum while other parts of the spectrum are inefficiently utilized. In cognitive radio environments, the primary users are allocated licensed frequency bands while secondary cognitive users dynamically allocate the empty frequencies within the licensed frequency band according to their requested QoS (Quality of Service) specifications. This dynamic decision-making is a multi-criteria optimization problem, which the authors propose to solve using a genetic algorithm. Genetic algorithms traverse the optimization search space using a multitude of parallel solutions and choosing the solution that has the best overall fit to the criteria. Due to this parallelism, the genetic algorithm is less likely than traditional algorithms to get caught at a local optimal point.

scholarly journals Image Encryption and Decryption using RSA Algorithm with Share Creation Techniques

2019 ◽  
Vol 8 (4) ◽  
pp. 2797-2800
Keyword(s):  
Image Encryption ◽  
Color Image ◽  
Visual Cryptography ◽  
Color Images ◽  
Blue Color ◽  
Image Sharing ◽  
Rsa Algorithm ◽  
Encryption And Decryption ◽  
Is Value

visual cryptography system proposed a image encryption and decryption method. In the proposed method Red, Green, Blue color images using visual cryptography. In existing system is working for share created, it is encrypted separately by using visual secret share creation (VSS) algorithms. The proposed work is original images share1 and ahare2 created XOR-Based visual cryptography. This proposed schemes share1 encryption and share2 encryption included in RSA algorithm. The share1 and ahare2 decryption process is enable secret image sharing and then stacking. The proposed system is value calculate the PSNR and MSE formula and then image security using NPCR and UACI formula. The visual cryptography existing work to compare the proposed work and better results quality of RGB color images. The color image encryption and decryption using RSA algorithm and matlab coding.

scholarly journals Optimization of Dempster-Shafer’s Believe Value Using Genetic Algorithm for Identification of Plant Diseases Jatropha Curcas

2018 ◽  
Vol 12 (1) ◽  
pp. 61
Author(s):  
Triando Hamonangan Saragih ◽  
Wayan Firdaus Mahmudy ◽  
Yusuf Priyo Anggodo
Keyword(s):  
Genetic Algorithm ◽  
Decision Making ◽  
Genetic Algorithms ◽  
Diesel Fuel ◽  
Jatropha Curcas ◽  
Plant Diseases ◽  
Extension Agents ◽  
The Difference ◽  
Lack Of Knowledge

<em><span>Jatropha curcas is a plant that can be used as a substitute for diesel fuel. Lack of knowledge of farmers and the limited number of experts and extension agents into the problem of dealing with the disease Jatropha curcas plant which resulted in lower quality of Jatropha curcas. Dempster-Shafer method can be a solution for decision making based on previous research. The difference in beliefs of every expert in seeing Jatropha diseases are important because Dempster-Shafer can not solve this problem. Optimization using genetic algorithms can solve this problem. Optimization of belief values using genetic algorithms can improve the accuracy of the results of this system are using Dempster-Shafer. On the results of this system provides the highest system accuracy value, opimization of belief values using genetic algorithms gives a more significant result than the use of Dempster-Shafer only.</span></em>

scholarly journals AES Image Encryption

2021 ◽  
Author(s):  
paavni gaur
Keyword(s):  
Image Encryption ◽  
Block Size ◽  
Image Data ◽  
Data Encryption ◽  
Key Generation ◽  
Iterative Approach ◽  
Secret Key ◽  
Unauthorized Access ◽  
Confidential Data ◽  
Encryption And Decryption

Abstract An Image Encryption and Decryption Using AES (Advance Encryption Standard) Algorithm is proposed in the project. Due to increasing use of image in various field, it is very important to protect the confidential image data from unauthorized access. The design uses the iterative approach with block size of 128 bit and key size of 128, 192 or 256 bit. The numbers of round for key size of 256 bits is 14, for 128 bits is 10 and for 192 bits is 12. As secret key increases the security as well as complexity of the cryptography algorithms. In this paper , an algorithm in which the image is an input to AES Encryption to get the encrypted image and then input it to AES Decryption to get the original image is proposed and explained which will further be implemented by me.The paper shows the study in which a system could be used for effective image data encryption and key generation in diversified application areas, where sensitive and confidential data needs to be transmitted along with the image.

Genetic Algorithm Learning of Nash Equilibrium

2015 ◽  
Vol 13 (3) ◽  
pp. 1-14 ◽  
Author(s):  
M'hamed Outanoute ◽  
Mohamed Baslam ◽  
Belaid Bouikhalene
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Quality Of Service ◽  
Nash Equilibrium ◽  
Service Providers ◽  
Optimization Methods ◽  
Great Power ◽  
Dynamical Behaviors ◽  
Game Theoretic

To select or change a service provider, customers use the best compromise between price and quality of service (QoS). In this work, the authors formulate a game theoretic framework for the dynamical behaviors of Service Providers (SPs). They share the same market and are competing to attract more customers to gain more profit. Due to the divergence of SPs interests, it is believed that this situation is a non-cooperative game of price and QoS. The game converges to an equilibrium position known Nash Equilibrium. Using Genetic Algorithms (GAs), the authors find strategies that produce the most favorable profile for players. GAs are from optimization methods that have shown their great power in the learning area. Using these meta-heuristics, the authors find the price and QoS that maximize the profit for each SP and illustrate the corresponding strategy in Nash Equilibrium (NE). They also show the influence of some parameters of the problem on this equilibrium.

OntoQuery-An Evolutionary Approach for Query Formation and Information Retrieval

2011 ◽  
pp. 140-160
Author(s):  
Sheng-Uei Guan ◽  
Chang Ching Chng ◽  
Fangming Zhu
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Information Retrieval ◽  
Query Optimization ◽  
Formation Process ◽  
Relevance Feedback ◽  
Fitness Function ◽  
Optimization Techniques ◽  
Retrieval Scheme

This chapter proposes the establishment of OntoQuery in an m-commerce agent framework. OntoQuery represents a new query formation approach that combines the usage of ontology and keywords. This approach takes advantage of the tree pathway structure in ontology to form queries visually and efficiently. Also, it uses keywords to complete the query formation process more efficiently. Present query optimization techniques like relevance feedback use expensive iterations. The proposed information retrieval scheme focuses on using genetic algorithms to improve computational effectiveness. Mutations are done on queries formed in the earlier part by replacing terms with synonyms. Query optimization techniques used include query restructuring by logical terms and numerical constraints replacement. Also, the fitness function of the genetic algorithm is defined by three elements, number of documents retrieved, quality of documents, and correlation of queries. The number and quality of documents retrieved give the basic strength of a mutated query.

Research on the Application of College Automated Course Scheduling System Based on Genetic Algorithm

2013 ◽  
Vol 760-762 ◽  
pp. 1782-1785
Author(s):  
Xiu Ying Li ◽  
Dong Ju Du
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Optimization Problem ◽  
Optimization Problems ◽  
Teaching Quality ◽  
Combinatorial Optimization Problem ◽  
Scheduling System ◽  
Course Scheduling ◽  
Strong Ability

A reasonable curriculum contributes to the improvement of the training and teaching quality of college students. Using computer which is speed and strong ability to arrange curriculum automatically is imperative. Automatically curriculum arrangement is a constrained, multi-objective and intricate combinatorial optimization problem. Based on genetic algorithm of population search, it is suitable to process complex and nonlinear optimization problems which it difficult to solve for traditional search methods. In this paper solves complex automated course scheduling using genetic algorithms.

Research on Assembly Optimization of Hull Section Based on the Genetic Algorithms

2013 ◽  
Vol 397-400 ◽  
pp. 1073-1077
Author(s):  
Wei Jun Xu ◽  
Long Kan Wang ◽  
Zhi Fan Zhang
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Virtual Assembly ◽  
Assembly Sequence ◽  
Section Model ◽  
Assembly Technology ◽  
Reducing Costs ◽  
Assembly Procedure ◽  
Optimal Assembly

This paper is concerned with the study on the assembly optimization of a hull section based on the genetic algorithms. It is significant important for improving efficiency of shipbuilding. Firstly, a typical hull section is selected as the analysis target for the assembly optimization. Then, the period and cost of shipbuilding is combined with the genetic algorithms, in which, the optimal assembly sequence is very important for the analysis, and it should be drown up. Finally, the hull section model is constructed by using CATIA software, and the simulation demo of the assembly procedure is carried out. The Genetic algorithm is a global optimizing method which can improve the calculation speed by using the subassembly. The virtual assembly of hull section based on the genetic algorithm is carried out under the environment of CATIA software, which including entity design, assembling and post-processing analysis and so on. The virtual assembly technology can be widely combined with the engineering production, not only have a significant effect on reducing costs and shortening the period of production, but also improve the quality of production. It is very useful for providing valuable reference in the actual productions.

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