Applying artificial intelligence in cybersecurity analytics and cyber threat detection
Material type:
TextLanguage: English Publication details: New Jersey: Wiley Data and Cybersecurity, 2024. Description: xxxiii, 327pISBN: 9781394196456Subject(s): Analysis of Malicious Executables and Detection Techniques | Artificial Intelligence Perspective on Digital Forensics | Detection and Analysis of Botnet Attacks Using Machine Learning TechniquesDDC classification: 005.83 Online resources: Click here to access online
| Item type | Current library | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|
| e-Books | Dr. S. R. Ranganathan Library Ebook (Online Access) | 005.83 (Online Access) (Browse shelf(Opens below)) | Available | EB0040 |
APPLYING ARTIFICIAL INTELLIGENCE IN CYBERSECURITY ANALYTICS AND CYBER THREAT DETECTION
Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML)
Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats.
Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter.
With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection explores topics such as:
Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis
Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering
How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats
Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint
Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cybersecurity Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.