Ethical Hacking Techniques And Countermeasures For Cybercrime Prevention
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Ethical Hacking Techniques and Countermeasures for Cybercrime Prevention
As personal data continues to be shared and used in all aspects of society, the protection of this information has become paramount. While cybersecurity should protect individuals from cyber-threats, it also should be eliminating any and all vulnerabilities. The use of hacking to prevent cybercrime and contribute new countermeasures towards protecting computers, servers, networks, web applications, mobile devices, and stored data from black hat attackers who have malicious intent, as well as to stop against unauthorized access instead of using hacking in the traditional sense to launch attacks on these devices, can contribute emerging and advanced solutions against cybercrime. Ethical Hacking Techniques and Countermeasures for Cybercrime Prevention is a comprehensive text that discusses and defines ethical hacking, including the skills and concept of ethical hacking, and studies the countermeasures to prevent and stop cybercrimes, cyberterrorism, cybertheft, identity theft, and computer-related crimes. It broadens the understanding of cybersecurity by providing the necessary tools and skills to combat cybercrime. Some specific topics include top cyber investigation trends, data security of consumer devices, phases of hacking attacks, and stenography for secure image transmission. This book is relevant for ethical hackers, cybersecurity analysts, computer forensic experts, government officials, practitioners, researchers, academicians, and students interested in the latest techniques for preventing and combatting cybercrime.
Computational Intelligence in Pattern Recognition
This book features high-quality research papers presented at the 6th International Conference on Computational Intelligence in Pattern Recognition (CIPR 2024), held at Maharaja Sriram Chandra Bhanja Deo University (MSCB University), Baripada, Odisha, India, during March 15–16, 2024. It includes practical development experiences in various areas of data analysis and pattern recognition, focusing on soft computing technologies, clustering and classification algorithms, rough set and fuzzy set theory, evolutionary computations, neural science and neural network systems, image processing, combinatorial pattern matching, social network analysis, audio and video data analysis, data mining in dynamic environments, bioinformatics, hybrid computing, big data analytics, and deep learning. It also provides innovative solutions to the challenges in these areas and discusses recent developments.
Artificial Intelligence of Health-Enabled Spaces
Artificial Intelligence of Health-Enabled Spaces (AIoH) has made a number of revolutionary advances in clinical studies that we are aware of. Among these advances, intelligent and medical services are gaining a great deal of interest. Nowadays, AI-powered technologies are not only used in saving lives, but also in our daily life activities in diagnosing, controlling, and even tracking of COVID-19 patients. These AI-powered solutions are expected to communicate with cellular networks smoothly in the next-generation networks (5G/6G and beyond) for more effective/critical medical applications. This will open the door for other interesting research areas. This book focuses on the development and analysis of artificial intelligence (AI) model applications across multiple disciplines. AI-based deep learning models, fuzzy and hybrid intelligent systems, and intrinsic explainable models are also presented in this book. Some of the fields considered in this smart health-oriented book include AI applications in electrical engineering, biomedical engineering, environmental engineering, computer engineering, education, cyber security, chemistry, pharmacy, molecular biology, and tourism. This book is dedicated to addressing the major challenges in fighting diseases and psychological issues using AI. These challenges vary from cost and complexity to availability and accuracy. The aim of this book is hence to focus on both the design and implementation aspects of AI-based approaches in the proposed health-related solutions. Targeted readers are from varying disciplines who are interested in implementing the smart planet/environments vision via intelligent enabling technologies.