Bio-inspired Computing Techniques for Data Security Challenges and Controls

Sripriyanka, G.; Mahendran, Anand

doi:10.1007/s42979-022-01292-w

Cited by 2 publications

(1 citation statement)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The second is the best global answer, which the swarm of particles has discovered thus far. As a result, each particle has its best personal answer, as well as the best global solution stored in its memory [38]- [40].…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Advanced Pitch Angle Control Based on Genetic Algorithm and Particle Swarm Optimisation on FAST Turbine Systems

Gorel,

Abdi

2023

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

In this paper, the increase in the quality of the rotor speed of wind turbines and the decrease in mechanical loads on the turbines are investigated. Adjusting the angle of the blade to the nominal wind speed, the rotor speed of the wind turbine is maintained at its nominal value. Using control methods (such as proportional integral (PI), genetic algorithms (GAs), and particle swarm optimisation (PSO)), different results can be recovered. In addition, individual control of the blade tilt angle allows us to reduce the mechanical loads on the turbine with the control methods. The wind turbine was modelled in Matlab/Simulink. The simulation results show that individual control of the blade tilt angle ensures the quality of the rotor speed of the wind turbine and reduces the balanced periodic loads on the wind turbine. In the first part, we study the wind turbine in a global way, as well as the method used to calculate them. Then, we discuss the FAST system, which was used to model the wind turbine, as well as the design of individual pitch angle control. As a result, it is possible to reduce the fatigue of the mechanical wind turbine parts. According to the study, the mechanical load for all three blades was reduced by an average of 44 % compared to the PI and PSO methods and by 1 % compared to the PI and GA methods. The control of the pitch angle in wind energy systems is performed with different control methods. The study analysis of the mechanical loads found that they are largely balanced. Winds that blow perpendicular to the turbine blades on the x-axis provide these loads.

show abstract

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Advanced Pitch Angle Control Based on Genetic Algorithm and Particle Swarm Optimisation on FAST Turbine Systems

Gorel,

Abdi

2023

ELEKTRON ELEKTROTECH

View full text Add to dashboard Cite

show abstract

Securing IoMT: A Hybrid Model for DDoS Attack Detection and COVID-19 Classification

Sripriyanka,

Mahendran

2024

IEEE Access

Self Cite

View full text Add to dashboard Cite

The coronavirus disease 2019 (COVID-19) epidemic had a momentous influence on the state of universal health and how people live their lives in every nation. The combination of the Internet of Things (IoT) with medical systems is referred to as the "Internet of Medical Things (IoMT)," and it makes it possible for various medical events to take place, including real-time medicine prescriptions, remote patient observing, and real-time diagnosis, amongst other things. However, the security, integrity, and concealment of medical data on the IoMT remain an endless issue, contributing to the difficulties that arise in providing medical services. However, these conventional methods failed to provide robust security against attacks like distributed denial of service (DDoS). As a result, security IoMT-based COVID-19 detection applications are required. Therefore, this article proposes a novel IoMT-based COVID-19 detection and classification network (ICDC-Net) for smart healthcare applications. Initially, Optimal Feistel Block Cipher (OFBC) encryption was performed on COVID-19-based medical data (chest x-ray images), which provides the highest security to the patient's data. Here, OFBC loss is optimized by the Hybrid Grey-Wolf Optimizer with Particle Swarm Optimization (HGWO-PSO), which performs DDoS attack detection and prevention. Further, the HGWO-PSO is also used to extract disease-specific features from the COVID-19 chest X-ray (CXR) images. Finally, the Residual Network50 (ResNet50) deep learning model is used to classify multiple diseases from CXR images, including normal, COVID-19, and viral pneumonia. The simulations disclosed that the proposed ICDC-Net resulted in improved attack detection accuracy (ADA), attack detection time (ADT), and reduced attack detection error rates (ADER) as compared to other security standards. Further, the simulations also disclosed that the proposed ICDC-Net developed superior COVID-19 categorization performing as equated to existing classification prototypes.

show abstract

Bio-inspired Computing Techniques for Data Security Challenges and Controls

Cited by 2 publications

References 65 publications

Advanced Pitch Angle Control Based on Genetic Algorithm and Particle Swarm Optimisation on FAST Turbine Systems

Advanced Pitch Angle Control Based on Genetic Algorithm and Particle Swarm Optimisation on FAST Turbine Systems

Securing IoMT: A Hybrid Model for DDoS Attack Detection and COVID-19 Classification

Contact Info

Product

Resources

About