Handbook Of Ai Driven Threat Detection And Prevention


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Handbook of AI-Driven Threat Detection and Prevention


Handbook of AI-Driven Threat Detection and Prevention

Author: Pankaj Bhambri

language: en

Publisher: CRC Press

Release Date: 2025-06-12


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In today’s digital age, the risks to data and infrastructure have increased in both range and complexity. As a result, companies need to adopt cutting-edge artificial intelligence (AI) solutions to effectively detect and counter potential threats. This handbook fills the existing knowledge gap by bringing together a team of experts to discuss the latest advancements in security systems powered by AI. The handbook offers valuable insights on proactive strategies, threat mitigation techniques, and comprehensive tactics for safeguarding sensitive data. Handbook of AI-Driven Threat Detection and Prevention: A Holistic Approach to Security explores AI-driven threat detection and prevention, and covers a wide array of topics such as machine learning algorithms, deep learning, natural language processing, and so on. The holistic view offers a deep understanding of the subject matter as it brings together insights and contributions from experts from around the world and various disciplines including computer science, cybersecurity, data science, and ethics. This comprehensive resource provides a well-rounded perspective on the topic and includes real-world applications of AI in threat detection and prevention emphasized through case studies and practical examples that showcase how AI technologies are currently being utilized to enhance security measures. Ethical considerations in AI-driven security are highlighted, addressing important questions related to privacy, bias, and the responsible use of AI in a security context. The investigation of emerging trends and future possibilities in AI-driven security offers insights into the potential impact of technologies like quantum computing and blockchain on threat detection and prevention. This handbook serves as a valuable resource for security professionals, researchers, policymakers, and individuals interested in understanding the intersection of AI and security. It equips readers with the knowledge and expertise to navigate the complex world of AI-driven threat detection and prevention. This is accomplished by synthesizing current research, insights, and real-world experiences.

Database Management using AI: A Comprehensive Guide


Database Management using AI: A Comprehensive Guide

Author: A Purushotham Reddy

language: en

Publisher: A Purushotham Reddy

Release Date: 2024-10-20


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Database Management Using AI: The Ultimate Guide for Data Professionals Database Management Using AI: A Comprehensive Guide is an essential resource for anyone eager to explore how artificial intelligence (AI) is revolutionizing the field of database management. This book caters to a wide audience, from database administrators, data scientists, and tech enthusiasts to professionals looking to integrate AI into their data management practices. It offers a professional yet easily understandable exploration of how AI is transforming modern data systems. The guide starts by laying a solid foundation in database management fundamentals, covering key concepts such as data models, SQL, and database design principles. It then delves into how AI can optimize database performance, enhance security, and automate complex tasks like data retrieval, query optimization, and schema design. With this book, readers will gain deep insights into integrating AI with traditional database systems and how AI tools are shaping the future of data management. Unlike other books that focus purely on theory, this guide stands out by emphasizing real-world applications. Through practical case studies, it demonstrates how AI-driven database systems are being leveraged across industries such as e-commerce, healthcare, finance, and logistics. These case studies show the real-world impact of AI, helping businesses increase efficiency, reduce errors, and make smarter, data-backed decisions. The book illustrates how AI is enabling organizations to stay ahead in a competitive market by harnessing the power of intelligent database management. Throughout the guide, readers will learn about the evolution of database systems, including the shift from relational databases to modern NoSQL databases, and how AI is enhancing traditional database models to meet the demands of the digital age. The book explores how AI integration in databases is transforming how data is processed and analyzed, automating repetitive tasks and improving the scalability and performance of databases. One of the key highlights of this book is the coverage of AI in database management. Readers will learn how AI is being used to automate routine database tasks, improve security by predicting and mitigating threats, and streamline database management operations through automation. Additionally, the book delves into how AI helps in predictive analytics and data mining, uncovering hidden patterns and enabling organizations to make accurate predictions based on large volumes of data. The book also covers predictive analytics and data mining, teaching readers how AI tools can be used to extract valuable insights from data, identify trends, and uncover business opportunities that were previously hard to detect. By understanding how AI can leverage data to drive business intelligence, readers will be able to implement AI-driven solutions that improve decision-making processes. Furthermore, this guide explores the future of database management with AI. It takes a close look at emerging trends, including autonomous databases and the growing role of cloud-based AI solutions in shaping the future of data management. These innovative technologies are creating intelligent, self-managing databases that are poised to revolutionize how data is stored, processed, and analyzed. Database Management Using AI provides readers with the knowledge and practical skills needed to navigate the fast-evolving landscape of AI-powered databases. Whether you're an industry professional or a student, this book is packed with actionable insights that will keep you ahead in the digital world. It’s a must-have resource for anyone looking to understand the practical impact of AI on database systems and harness the power of machine learning, big data, and cloud computing to transform their approach to data management. With its combination of clear explanations, real-world case studies, and forward-looking insights, this book is the ultimate guide for anyone wanting to stay competitive in the digital age. Database Management Using AI is more than just a book—it's an essential tool for anyone serious about mastering the future of data systems. Refer www.latest2all.com for details...

AI in Cybersecurity


AI in Cybersecurity

Author: Leslie F. Sikos

language: en

Publisher: Springer

Release Date: 2018-09-27


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This book presents a collection of state-of-the-art AI approaches to cybersecurity and cyberthreat intelligence, offering strategic defense mechanisms for malware, addressing cybercrime, and assessing vulnerabilities to yield proactive rather than reactive countermeasures. The current variety and scope of cybersecurity threats far exceed the capabilities of even the most skilled security professionals. In addition, analyzing yesterday’s security incidents no longer enables experts to predict and prevent tomorrow’s attacks, which necessitates approaches that go far beyond identifying known threats. Nevertheless, there are promising avenues: complex behavior matching can isolate threats based on the actions taken, while machine learning can help detect anomalies, prevent malware infections, discover signs of illicit activities, and protect assets from hackers. In turn, knowledge representation enables automated reasoning over network data, helping achieve cybersituational awareness. Bringing together contributions by high-caliber experts, this book suggests new research directions in this critical and rapidly growing field.