AI-Driven Cybersecurity and Threat Intelligence Cyber Automation, Intelligent Decision-Making and Explainability /
This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how on...
Saved in:
| Main Author: | |
|---|---|
| Corporate Author: | |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2024.
|
| Edition: | 1st ed. 2024. |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-031-54497-2 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
MARC
| LEADER | 00000nam a22000005i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-54497-2 | ||
| 003 | DE-He213 | ||
| 005 | 20260810170337.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 240428s2024 sz | o |||| 0|eng d | ||
| 020 | |a 9783031544972 |9 978-3-031-54497-2 | ||
| 024 | 7 | |a 10.1007/978-3-031-54497-2 |2 doi | |
| 050 | 4 | |a TK5105.59 | |
| 072 | 7 | |a UTN |2 bicssc | |
| 072 | 7 | |a COM043050 |2 bisacsh | |
| 072 | 7 | |a UTN |2 thema | |
| 082 | 0 | 4 | |a 005.8 |2 23 |
| 100 | 1 | |a Sarker, Iqbal H. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a AI-Driven Cybersecurity and Threat Intelligence |h [electronic resource] : |b Cyber Automation, Intelligent Decision-Making and Explainability / |c by Iqbal H. Sarker. |
| 250 | |a 1st ed. 2024. | ||
| 264 | 1 | |a Cham : |b Springer Nature Switzerland : |b Imprint: Springer, |c 2024. | |
| 300 | |a 1 online resource (XVII, 200 p. 43 illus.). |b 29 illus. in color. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 341 | 0 | |b Table of contents navigation |2 onix | |
| 341 | 0 | |b Single logical reading order |2 onix | |
| 341 | 0 | |b Short alternative textual descriptions |2 onix | |
| 341 | 0 | |b Use of color is not sole means of conveying information |2 onix | |
| 341 | 0 | |b Use of high contrast between text and background color |2 onix | |
| 341 | 0 | |b Next / Previous structural navigation |2 onix | |
| 341 | 0 | |b All non-decorative content supports reading without sight |2 onix | |
| 347 | |a text file |b PDF |2 rda | ||
| 505 | 0 | |a Part I Preliminaries -- 1. Introduction to AI-Driven Cybersecurity and Threat Intelligence -- 2. Cybersecurity Background Knowledge: Terminologies, Attack Frameworks and Security Life Cycle -- Part II AI/XAI Methods and Emerging Technologies -- 3. Learning Technologies: Towards Machine Learning and Deep Learning for Cybersecurity -- 4. Detecting Anomalies and Multi-Attacks through Cyber Learning: An Experimental Analysis -- 5. Generative AI for Cybersecurity -- 6. Cybersecurity Data Science: Towards Advanced Analytics, Knowledge and Rule Discovery for Explainable AI Modeling -- Part III Real-World Application Areas with Research Issues -- 7. AI-Enabled Cybersecurity for IoT and Smart City Applications -- 8. AI for Enhancing ICS/OT Cybersecurity -- 9. AI for Critical Infrastructure Protection and Resilience -- 10. CyberAI: A Comprehensive Summary of AI Variants, Explainable and Responsible AI for Cybersecurity. | |
| 520 | |a This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world. Overall, the use of AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book. | ||
| 532 | 8 | |a Accessibility summary: This PDF does not fully comply with PDF/UA standards, but does feature limited screen reader support, described non-text content (images, graphs), bookmarks for easy navigation and searchable, selectable text. Users of assistive technologies may experience difficulty navigating or interpreting content in this document. We recognize the importance of accessibility, and we welcome queries about accessibility for any of our products. If you have a question or an access need, please get in touch with us at accessibilitysupport@springernature.com. | |
| 532 | 8 | |a No reading system accessibility options actively disabled | |
| 532 | 8 | |a Publisher contact for further accessibility information: accessibilitysupport@springernature.com | |
| 588 | |a Print version record. | ||
| 650 | 0 | |a Computer networks |x Security measures. | |
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Machine learning. | |
| 650 | 1 | 4 | |a Mobile and Network Security. |
| 650 | 2 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Machine Learning. |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9783031544965 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031544989 |
| 776 | 0 | 8 | |i Printed edition: |z 9783031544996 |
| 856 | 4 | 0 | |u https://doi.org/10.1007/978-3-031-54497-2 |
| 912 | |a ZDB-2-SCS | ||
| 912 | |a ZDB-2-SXCS | ||
| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||