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Wireless Communication in Cyber Security

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  • Дата: 20-04-2024, 05:21
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Название: Wireless Communication in Cyber Security
Автор: S. Sountharrajan, R. Maheswar, Geetanjali Rathee
Издательство: Wiley-Scrivener
Год: 2023
Страниц: 284
Язык: английский
Формат: pdf (true)
Размер: 15.7 MB

Presenting the concepts and advances of wireless communication in cybersecurity, this volume, written and edited by a global team of experts, also goes into the practical applications for the engineer, student, and other industry professionals.

Rapid advancement in wireless communications and related technologies has led to the use of newer technologies like 6G, Internet of Things (IoT), Radar, and others. Not only are the technologies expanding, but the impact of wireless communication is also changing, becoming an inevitable part of daily life. With increased use comes great responsibilities and challenges for any newer technology. The growing risks in the direction of security, authentication, and encryption are some major areas of concern, together with user privacy and security. We have seen significant development in blockchain technology along with development in a wireless network that has proved extremely useful in solving various security issues. Quite efficient secure cyber-physical systems can be constructed using these technologies.

This comprehensive new volume covers the many methods and technologies used in intrusion detection in wireless networks. This book allows readers to reach their solutions using various predictive algorithm-based approaches and some curated real-time protective examples that are defined herein. Artificial Intelligence (AI) concepts are devised and proposed for helping readers understand the core concepts of efficiencies of threats, and the parallel solutions are covered. The chapters also state the challenges in privacy and security levels for various algorithms and various techniques and tools are proposed for each challenge. It focuses on providing exposure to readers about data security and privacy for wider domains.

Traditional data communication networking is not suitable for industry 4.0. So industry moves to implement software-defined networks for managing the networks. But security is an important thread in a software-defined network. Most attackers are easily getting access to the resource in the industry. The Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks cause heavy damage in the production area. Malicious attacks will create a services gap; network services throughput enter into a down state, and there is a loss in business continuity. Traditional Intrusion Detection System (IDS) will detect malicious traffic based on a predefined access control list but it cannot detect new malicious traffic ingress into home networks. Machine learning techniques will lead to better identification of threats to synthetic or real-time data. To avoid these situations, we are proposing a model to find the attackers in the network and train the model to find the new type of intruder in the system.

Artificial Intelligence incorporates human intelligence into machines and builds statistical models for providing solutions in various domains like cybersecurity. Though the AI-based techniques for detecting cyberattacks and threats are more efficient than traditional cybersecurity techniques, they lack explainability. These methods provide black-box solutions that are not transparent and interpretable in understanding the steps involved in reaching specific predictions. This reduces the confidence of users in the models used for cybersecurity, particularly in the present scenarios where cyberattacks are becoming increasingly diverse and complicated. To overcome this, Explainable Artificial Intelligence (XAI) is applied, which eventually replaces the traditional artificial, Machine Learning, and Deep Learning algorithms that operate as a black box. Given that cyberattacks are increasing day by day and the traditional AI algorithms are not sufficient for providing security, it is essential to focus more on XAI for exploiting the AI algorithms. This chapter provides a detailed discussion about explainable artificial intelligence and how it is applied in providing cybersecurity.

The editorial and author team aims to address all possible solutions to the various problems faced in the newer techniques of wireless communications, improving the accuracies and reliability over the possible vulnerabilities and security threats to wireless communications. It is a must have for any engineer, scientist, or other industry professional working in this area.

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