Nature-Inspired Optimization Algorithms

Recent Advances in Natural Computing and Biomedical Applications

Aditya Khamparia, Ashish Khanna, Nhu Gia Nguyen, Bao Le Nguyen, Aditya Khamparia, Ashish Khanna, Nhu Gia Nguyen, Bao Le Nguyen

• Éditeur: De Gruyter
• Année: 2021
• ISBN:
  9783110676150
• Édition: 1
• Sujet: Informatik
• Sous-sujet: Künstliche Intelligenz (KI) & Semantik

This book will focus on the involvement of data mining and intelligent computing methods for recent advances in Biomedical applications and algorithms of nature-inspired computing for Biomedical systems. The proposed meta heuristic or nature-inspired techniques should be an enhanced, hybrid, adaptive or improved version of basic algorithms in terms of performance and convergence metrics. In this exciting and emerging interdisciplinary area a wide range of theory and methodologies are being investigated and developed to tackle complex and challenging problems.

Today, analysis and processing of data is one of big focuses among researchers community and information society. Due to evolution and knowledge discovery of natural computing, related meta heuristic or bio-inspired algorithms have gained increasing popularity in the recent decade because of their significant potential to tackle computationally intractable optimization dilemma in medical, engineering, military, space and industry fields. The main reason behind the success rate of nature inspired algorithms is their capability to solve problems. The nature inspired optimization techniques provide adaptive computational tools for the complex optimization problems and diversified engineering applications.

Tentative Table of Contents/Topic Coverage:

- Neural Computation

- Evolutionary Computing Methods

- Neuroscience driven AI Inspired Algorithms

- Biological System based algorithms

- Hybrid and Intelligent Computing Algorithms

- Application of Natural Computing

- Review and State of art analysis of Optimization algorithms

- Molecular and Quantum computing applications

- Swarm Intelligence

- Population based algorithm and other optimizations

1 Selecting and assessing the importance of malware analysis methods for web-based biomedical services through fuzzy-based decision-making procedure

Abhishek Kumar Pandey

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

Ashutosh Tripathi

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

Alka Agrawal

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

Rajeev Kumar

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

Department of Computer Application, Shri Ramswaroop Memorial University, Lucknow-Deva Road, Barabanki, Uttar Pradesh, India

Raees Ahmad Khan

Department of Information Technology, Babasaheb Bhimrao Ambedkar University, Lucknow, Uttar Pradesh, India

Abstract

Malware is continuously penetrating the current digital world. Even more alarming are the statistics that reveal that the biomedical industry is presently the most susceptible target of the attackers. The main reasons behind this disquieting situation of attacks on the biomedical industry are its sensitivity level and impact of harm. Moreover, the high cost of medical records is also a major reason for the upsurge in penetration and exploitation. This scenario calls for an effective prevention mechanism to ward off malware attacks on the biomedical or healthcare industry. This research initiative provides an overview of recent statistics of malware attacks in web-based biomedical applications and services. The study also provides a helpful mechanism called malware analysis for preventing malware issues. Further, the study analyzes the malware analysis approach for better and easy understanding and, more importantly, its adoption in biomedical industry. It also provides a ranking assessment/priority assessment of different malware analysis techniques for identifying the most prioritized approach through fuzzy analytic hierarchy process methodology. The study uses a scientifically proven approach for prioritization of analysis techniques and provides a novel idea and path for future researchers.

Keywords: malware, malware analysis, fuzzy logic, AHP, prioritization,

1.1 Introduction

Malware is the biggest threat for every web-based industry and service. Malware can be more aptly described as the termite that infests digital systems in the current computer era. From sensitive data manipulation to a system failure condition, malware attacks cause all types of damage. The damage percentage is relatively very high in the case of malware exploits when compared with other vulnerability exploits and attacks. A study shows that there has been a sizeable growth of 61% in malicious activities in 2019, when co...

Table des matières

• Title Page
• Copyright
• Contents
•  1 Selecting and assessing the importance of malware analysis methods for web-based biomedical services through fuzzy-based decision-making procedure
• 2 A medical intelligent system for diagnosis of chronic kidney disease using adaptive neuro-fuzzy inference system
• 3 Contrast enhancement approach for satellite images using hybrid fusion technique and artificial bee colony optimization
• 4 Role of intelligent IoT applications in fog computing
• 5 Energy-efficient routing employing neural networks along with vector-based pipeline in underwater wireless sensor networks
• 6 A review of global optimization problems using meta-heuristic algorithm
• 7 Secure indexing and storage of big data
• 8 Genetic algorithm and normalized text feature based document classification
• 9 Nature-inspired optimization techniques
• Index
• Computational Intelligence for Machine Learning and Healthcare Informatics