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Методы, реализация и применение разведки и аналитики кибербезопасности
Cyber security is a key focus in the modern world as more private information is stored and saved online. In order to ensure vital information is protected from various cyber threats, it is essential to develop a thorough understanding of technologies that can address cyber security challenges. Artificial intelligence has been recognized as an important technology that can be employed successfully in the cyber security sector. Due to this, further study on the potential uses of artificial intelligence is required. Methods, Implementation, and Application of Cyber Security Intelligence and Analytics discusses critical artificial intelligence technologies that are utilized in cyber security and considers various cyber security issues and their optimal solutions supported by artificial intelligence. Covering a range of topics such as malware, smart grid, data breachers, and machine learning, this major reference work is ideal for security analysts, cyber security specialists, data analysts, security professionals, computer scientists, government officials, researchers, scholars, academicians, practitioners, instructors, and students.
Chapter 1 explores the fundamental idea towards cybersecurity and cyber intelligence. These chapters are written for educators, practitioners, professionals who want an overview of cyber security which provides insights of understanding of cyber security and its impact on economy. This chapter walks through foundation of cyber security by highlighting its framework, challenges, other application areas of cyber security which transforms society and so on.
Chapter 2 describes the Emerging Trends in Cyber Security. The increasing sophistication of these attacks has prompted numerous organizations to crack down on cybercriminals, resulting in the back-and-forth that characterizes today's cybersecurity trends. For-profit and charitable businesses alike are losing billions of dollars due to security flaws. The bulk of corporations, institutions, and other working professions are being pushed to migrate to remote work. To keep the job going, many new enterprises, institutions, and IT farms must shift to remote working areas quickly and without sufficient planning. This unanticipated movement allows security measures to be bypassed, increasing risk and susceptibility. It has become fashionable to circumvent security measures to gain speedy access, hence increasing cybercrime.
In Chapter 3 the major role of AI-ML Techniques in Cyber Security is presented. Anomaly detection can be used by AI and ML approaches to detect suspicious behavior such as unidentified devices joining a network, anomalous network traffic, and so on. Furthermore, AI and machine learning may detect host-based anomalies such as high CPU consumption, which can indicate the presence of malware.
In Chapter 4 brief out how Machine Learning (ML) Methods are used to Identify Data Breaches. Although we hear a lot about major cybersecurity breaches in non-insurance organizations – Target, Experian, the IRS, and so on – there have also been breaches in the insurance industry, albeit in a less publicized manner. Regardless of how hard organizations try to secure their data and systems, hackers' methods of breaching continue to evolve. This is why risk management and insurance innovation are so critical. Machine learning can collect and process massive amounts of data, analyze historical cyber-attacks, predict the types that may occur, and set up defenses against them.
In Chapter 5 brief out How Cyber Threat Intelligence (CTI) ensures Cyber Resilience using Artificial Intelligence and Machine Learning. Cyber Intelligence is the ability to prevent or mitigate cyber-attacks by studying threat data and providing information on adversaries. It aids in the identification, preparation, and prevention of attacks by providing information on attackers, their motivations, and their capabilities...
Chapter 1: Introduction to Cyber Security
Chapter 2: Emerging Challenges in Cyber Security
Chapter 3: The Role of AI-ML Techniques in Cyber Security
Chapter 4: Machine Learning (ML) Methods to Identify Data Breaches
Chapter 5: How Cyber Threat Intelligence (CTI) Ensures Cyber Resilience Using Artificial Intelligence and Machine Learning
Chapter 6: Cyber Security for Smart Grids
Chapter 7: The Fifth and the Sixth Order Gopala Hemachandra Representations and the Use of These Representations in Symmetric Cryptography
Chapter 8: Data Encryption and Hiding for Secured Data Transmission
Chapter 9: Artificial Intelligence-Based Billing System
Chapter 10: Emerging Computing Platforms for Solving Complex Engineering Problems
Chapter 11: Data-Driven Android Malware Analysis Intelligence
Chapter 12: Entropy-Based Feature Selection for Network Intrusion Detection Systems
Chapter 13: Recognizing User Portraits for Fraudulent Identification on Online Social Networks