Computational Intelligence for Cybersecurity Management and Applications

Machine intelligence techniques and methods are used to protect cybersecurity and privacy, with case studies and applications in Smart Cities, IoT, Cyber Physical Systems, and more.

Format: Hardback
Length: 236 pages
Publication date: 28 April 2023
Publisher: Taylor & Francis Ltd

Here is the rephrased text:
Machine intelligence (MI) has revolutionized the field of cybersecurity and privacy, offering new techniques and methods to enhance security and protect sensitive data. In this article, we will explore the latest discoveries in MI techniques and methods for cybersecurity and privacy.

Case studies and applications of machine intelligence in various cybersecurity fields are crucial in understanding the practical implications of MI in the real world. From smart cities to the Internet of Things (IoT), cyber physical systems, and beyond, MI has the potential to address complex cybersecurity challenges and improve the overall security posture of organizations.

Combining theory and practice is essential for making machine intelligence for cybersecurity accessible to readers of all levels. This means providing a clear description of the concepts and context related to MI, as well as practical examples and case studies that demonstrate how MI can be implemented in real-world scenarios.

One of the latest discoveries in MI for cybersecurity is the use of deep learning algorithms. Deep learning is a subset of machine learning that involves training neural networks to recognize patterns and make predictions based on large amounts of data. Deep learning algorithms have been used in various cybersecurity applications, such as image recognition, natural language processing, and anomaly detection.

Another area of focus in MI for cybersecurity is the use of blockchain technology. Blockchain is a distributed ledger technology that enables secure and transparent transactions between multiple parties. By leveraging blockchain, organizations can create secure and tamper-proof systems for storing and managing sensitive data.

Machine learning algorithms are also being used to analyze large amounts of cybersecurity data and identify patterns that indicate potential threats. This data-driven approach allows organizations to prioritize their resources and respond to threats more effectively.

In addition to these techniques, machine intelligence is also being used to improve the security of cloud computing environments. Cloud computing is a popular technology for storing and processing sensitive data, but it also poses several security challenges. Machine learning algorithms can be used to detect and prevent cyberattacks in cloud environments, such as identity theft, data breaches, and ransomware attacks.

Another area of application for machine intelligence in cybersecurity is the use of autonomous systems. Autonomous systems, such as self-driving cars and drones, are increasingly being used in various industries, including cybersecurity. Machine learning algorithms can be used to train autonomous systems to identify and respond to potential threats, reducing the risk of human error and improving the overall security posture of organizations.

In conclusion, machine intelligence has the potential to transform the field of cybersecurity and privacy. By leveraging the latest discoveries in MI techniques and methods, organizations can enhance their security posture and protect sensitive data from potential threats. Case studies and applications of machine intelligence in various cybersecurity fields provide practical examples of how MI can be implemented in real-world scenarios. Combining theory and practice is essential for making machine intelligence for cybersecurity accessible to readers of all levels. As the field of MI continues to evolve, we can expect to see even more innovative and effective solutions for cybersecurity and privacy.

Dimension: 234 x 156 (mm)
ISBN-13: 9781032335032