A Novel Approach to Generate Symmetric Key in Cryptography Using Genetic Algorithm (GA)

2018 ◽  
pp. 713-724 ◽  
Author(s):  
Chukhu Chunka ◽  
Rajat Subhra Goswami ◽  
Subhasish Banerjee
Keyword(s):  
Genetic Algorithm ◽  
Novel Approach ◽  
Symmetric Key

scholarly journals A Novel Approach of Symmetric Key Cryptography using Genetic Algorithm Implemented on GPGPU

Cryptography ◽  
2020 ◽  
pp. 193-213
Author(s):  
Srinivasa K. G. ◽  
Siddesh G. M. ◽  
Srinidhi Hiriyannaiah ◽  
Anusha Morappanavar ◽  
Anurag Banerjee
Keyword(s):  
Genetic Algorithm ◽  
Digital Communication ◽  
The Internet ◽  
Internet Applications ◽  
Unauthorized Access ◽  
Novel Approach ◽  
The World ◽  
Symmetric Key ◽  
Cuda Architecture ◽  
Symmetric Key Cryptography

The world of digital communication consists of various applications which uses internet as the backbone for communication. These applications consist of data related to the users of the application, which is confidential and integrity needs to be maintained to protect against unauthorized access and use. In the information hiding field of research, Cryptography is one of the wide techniques used to provide security to the internet applications that overcome the challenges like confidentiality, integrity, authentication services etc. In this paper, we present a novel approach on symmetric key cryptography technique using genetic algorithm that is implemented on CUDA architecture.

A Novel Approach of Symmetric Key Cryptography using Genetic Algorithm Implemented on GPGPU

2016 ◽  
pp. 283-303
Author(s):  
Srinivasa K. G. ◽  
Siddesh G. M. ◽  
Srinidhi Hiriyannaiah ◽  
Anusha Morappanavar ◽  
Anurag Banerjee
Keyword(s):  
Genetic Algorithm ◽  
Digital Communication ◽  
The Internet ◽  
Internet Applications ◽  
Unauthorized Access ◽  
Novel Approach ◽  
The World ◽  
Symmetric Key ◽  
Cuda Architecture ◽  
Symmetric Key Cryptography

The world of digital communication consists of various applications which uses internet as the backbone for communication. These applications consist of data related to the users of the application, which is confidential and integrity needs to be maintained to protect against unauthorized access and use. In the information hiding field of research, Cryptography is one of the wide techniques used to provide security to the internet applications that overcome the challenges like confidentiality, integrity, authentication services etc. In this paper, we present a novel approach on symmetric key cryptography technique using genetic algorithm that is implemented on CUDA architecture.

A novel identification approach for shearer running status through integration of rough sets and improved wavelet neural network

2016 ◽  
Vol 230 (16) ◽  
pp. 2792-2805 ◽  
Author(s):  
Lei Si ◽  
Zhongbin Wang ◽  
Xinhua Liu
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Rough Sets ◽  
Particle Swarm Optimization Algorithm ◽  
Wavelet Neural Network ◽  
Decision Table ◽  
Swarm Optimization ◽  
Novel Approach ◽  
Identification Approach ◽  
Simulation Results

In order to accurately and conveniently identify the shearer running status, a novel approach based on the integration of rough sets (RS) and improved wavelet neural network (WNN) was proposed. The decision table of RS was discretized through genetic algorithm and the attribution reduction was realized by MIBARK algorithm to simply the samples of WNN. Furthermore, an improved particle swarm optimization algorithm was proposed to optimize the parameters of WNN and the flowchart of proposed approach was designed. Then, a simulation example was provided and some comparisons with other methods were carried out. The simulation results indicated that the proposed approach was feasible and outperforming others. Finally, an industrial application example of mining automation production was demonstrated to verify the effect of proposed system.

Algorithmic music generation by harmony recombination with genetic algorithm

2021 ◽  
pp. 1-13
Author(s):  
Omar Lopez-Rincon ◽  
Oleg Starostenko ◽  
Alejandro Lopez-Rincon
Keyword(s):  
Genetic Algorithm ◽  
New Music ◽  
Novel Approach ◽  
Time Patterns ◽  
Algorithmic Music ◽  
Long Time ◽  
Music Generation ◽  
Music Piece ◽  
Short Time ◽  
Algorithmic Music Composition

Algorithmic music composition has recently become an area of prestigious research in projects such as Google’s Magenta, Aiva, and Sony’s CSL Lab aiming to increase the composers’ tools for creativity. There are advances in systems for music feature extraction and generation of harmonies with short-time and long-time patterns of music style, genre, and motif. However, there are still challenges in the creation of poly-instrumental and polyphonic music, pieces become repetitive and sometimes these systems copy the original files. The main contribution of this paper is related to the improvement of generating new non-plagiary harmonic developments constructed from the symbolic abstraction from MIDI music non-labeled data with controlled selection of rhythmic features based on evolutionary techniques. Particularly, a novel approach for generating new music compositions by replacing existing harmony descriptors in a MIDI file with new harmonic features from another MIDI file selected by a genetic algorithm. This allows combining newly created harmony with a rhythm of another composition guaranteeing the adjustment of a new music piece to a distinctive genre with regularity and consistency. The performance of the proposed approach has been assessed using artificial intelligent computational tests, which assure goodness of the extracted features and shows its quality and competitiveness.

scholarly journals A Genetic Algorithm Approach for Group Recommender System Based on Partial Rankings

2018 ◽  
Vol 29 (1) ◽  
pp. 653-663 ◽  
Author(s):  
Ritu Meena ◽  
Kamal K. Bharadwaj
Keyword(s):  
Genetic Algorithm ◽  
Recommender Systems ◽  
Rank Aggregation ◽  
Partial Ranking ◽  
Novel Approach ◽  
Kendall Tau Distance ◽  
Ultimate Objective ◽  
Aggregation Technique ◽  
The Individual ◽  
Group Recommender

Abstract Many recommender systems frequently make suggestions for group consumable items to the individual users. There has been much work done in group recommender systems (GRSs) with full ranking, but partial ranking (PR) where items are partially ranked still remains a challenge. The ultimate objective of this work is to propose rank aggregation technique for effectively handling the PR problem. Additionally, in real applications, most of the studies have focused on PR without ties (PRWOT). However, the rankings may have ties where some items are placed in the same position, but where some items are partially ranked to be aggregated may not be permutations. In this work, in order to handle problem of PR in GRS for PRWOT and PR with ties (PRWT), we propose a novel approach to GRS based on genetic algorithm (GA) where for PRWOT Spearman foot rule distance and for PRWT Kendall tau distance with bucket order are used as fitness functions. Experimental results are presented that clearly demonstrate that our proposed GRS based on GA for PRWOT (GRS-GA-PRWOT) and PRWT (GRS-GA-PRWT) outperforms well-known baseline GRS techniques.

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