Hybrid data encryption model integrating multi-objective adaptive genetic algorithm for secure medical data communication over cloud-based healthcare systems

2021 ◽  
Author(s):  
R. Denis ◽  
P. Madhubala
Keyword(s):  
Genetic Algorithm ◽  
Data Communication ◽  
Healthcare Systems ◽  
Data Encryption ◽  
Medical Data ◽  
Adaptive Genetic Algorithm ◽  
Multi Objective ◽  
Hybrid Data

Multi-Objective Fleet Assignment Problem Based on Self-Adaptive Genetic Algorithm

2013 ◽  
Vol 694-697 ◽  
pp. 2895-2900 ◽  
Author(s):  
Xiao Yang ◽  
Bo Jiang
Keyword(s):  
Genetic Algorithm ◽  
Carbon Emissions ◽  
Assignment Problem ◽  
Network Capacity ◽  
Total Carbon ◽  
Adaptive Genetic Algorithm ◽  
Multi Objective ◽  
Route Network ◽  
Assignment Model ◽  
Key Factor

Since the beginning of the twenty-first century, energy conservation has become the theme of the development of the world. China government set the emissions-reduction targets in various industries on the 12th Five-Year Plan. And the airlines were committed to reduce their carbon emissions. From an operational perspective, the airline model assignment problem is a key factor of the total carbon emissions on the entire route network. But the traditional aircraft assignment models approach did not account for this purpose to reduce carbon emissions. By constructing the multi-objective optimization models consider carbon emissions assignment model using a genetic algorithm, numerical example shows that the model is able to meet all aspects demand which include meeting route network capacity demand, minimizing operating costs and reducing total aircraft fleet carbon emissions.

scholarly journals Features of genetic algorithm for plain text encryption

2021 ◽  
Vol 11 (1) ◽  
pp. 434
Author(s):  
Riyadh Bassil Abduljabbar ◽  
Oday Kamil Hamid ◽  
Nazar Jabbar Alhyani
Keyword(s):  
Genetic Algorithm ◽  
Data Transmission ◽  
High Speed ◽  
Data Communication ◽  
Data Encryption ◽  
Genetic Operators ◽  
Plain Text ◽  
Secured Data ◽  
And Storage ◽  
Crossover And Mutation

The data communication has been growing in present day. Therefore, the data encryption became very essential in secured data transmission and storage and protecting data contents from intruder and unauthorized persons. In this paper, a fast technique for text encryption depending on genetic algorithm is presented. The encryption approach is achieved by the genetic operators Crossover and mutation. The encryption proposal technique based on dividing the plain text characters into pairs, and applying the crossover operation between them, followed by the mutation operation to get the encrypted text. The experimental results show that the proposal provides an important improvement in encryption rate with comparatively high-speed Processing.

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