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    Ai In Cybersecurity: The Complete Overview

    Posted By: ELK1nG
    Ai In Cybersecurity: The Complete Overview

    Ai In Cybersecurity: The Complete Overview
    Published 7/2025
    MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
    Language: English | Size: 783.34 MB | Duration: 4h 33m

    Learn how Artificial Intelligence is revolutionizing threat detection, incident response, and vulnerability management.

    What you'll learn

    Explain the core concepts of AI and Machine Learning and their specific applications within the cybersecurity domain.

    Analyze how AI is used for threat detection, including malware, network intrusions, and phishing attempts.

    Evaluate AI's role in vulnerability management, from predicting weaknesses to automating security patching and penetration testing.

    Describe adversarial AI attacks and the strategies used to defend AI systems against them.

    Requirements

    A foundational understanding of basic cybersecurity principles and IT concepts is recommended. No prior experience with AI or programming is required.

    Description

    Welcome to the definitive overview of Artificial Intelligence in Cybersecurity. In an era where digital threats are becoming more sophisticated and voluminous, traditional security measures are struggling to keep up. This is where AI comes in, offering a transformative approach to detecting, preventing, and responding to cyberattacks. This course provides a comprehensive but accessible exploration of how AI and Machine Learning are being deployed to create more resilient, intelligent, and automated security solutions.Throughout this course, you will journey from the fundamental principles of AI to its most advanced applications in the security landscape. We begin by demystifying AI and Machine Learning, establishing a solid foundation of core concepts tailored specifically for a cybersecurity context. You will understand not just what AI is, but why it has become an indispensable tool for security professionals. We will also have an honest discussion about the limitations and crucial ethical considerations surrounding the use of AI in security.The course then dives deep into the practical applications of AI across key cybersecurity domains. You will learn how AI-powered algorithms are outsmarting malware, how network intrusion detection systems (NIDS) leverage machine learning to spot anomalous behavior in real-time, and how AI is supercharging the fight against phishing and spam. We'll explore User Behavior Analytics (UBA) to see how AI can identify insider threats by learning what's 'normal' and flagging what's not.Next, we'll shift our focus to proactive defense with AI in Vulnerability Management. Discover how AI can analyze code for security flaws, predict which vulnerabilities pose the greatest risk to your organization, and even automate aspects of penetration testing and security patching, significantly reducing your window of exposure.When an incident does occur, speed is critical. You will see how AI is revolutionizing Incident Response by automating the triage of endless security alerts, orchestrating complex response workflows through SOAR platforms, and accelerating forensic investigations to pinpoint the root cause of a breach faster than ever before.But it's not just about defense. We will also explore the dark side: Adversarial AI. You'll gain a crucial understanding of how attackers are targeting AI systems themselves with sophisticated techniques like evasion and data poisoning. More importantly, you'll learn the strategies and best practices for defending your AI models from these advanced threats.Finally, we bring it all together by providing a practical roadmap for implementing AI security solutions in your own organization. We'll cover how to choose the right tools, integrate them into your existing security stack, and measure the return on investment (ROI) of your AI security initiatives.By the end of this course, you will have a holistic understanding of the AI cybersecurity ecosystem. You will be able to confidently discuss AI security concepts, evaluate AI-driven tools, and understand the strategic implications of adopting AI for protecting your organization's critical assets.

    Overview

    Section 1: Introduction

    Lecture 1 Welcome

    Section 2: AI Cybersecurity Fundamentals

    Lecture 2 What is AI and Machine Learning

    Lecture 3 Core AI Concepts for Security

    Lecture 4 The Role of AI in Cybersecurity

    Lecture 5 Limitations and Ethical Considerations

    Section 3: AI for Threat Detection

    Lecture 6 AI-Powered Malware Detection

    Lecture 7 Network Intrusion Detection with AI

    Lecture 8 AI in Phishing and Spam Filtering

    Lecture 9 User Behavior Analytics for Threats

    Section 4: AI in Vulnerability Management

    Lecture 10 AI for Code and Application Security

    Lecture 11 Predicting and Prioritizing Vulnerabilities

    Lecture 12 Automating Penetration Testing with AI

    Lecture 13 AI-Driven Security Patching

    Section 5: AI for Incident Response

    Lecture 14 Automating Security Alert Triage

    Lecture 15 AI-Powered Security Orchestration SOAR

    Lecture 16 Speeding Up Incident Investigation

    Lecture 17 AI in Digital Forensics

    Section 6: The Other Side: Adversarial AI

    Lecture 18 Understanding Adversarial Attacks on AI

    Lecture 19 Evasion Poisoning and Inference Attacks

    Lecture 20 Defending AI Systems From Attacks

    Lecture 21 The Future of AI vs AI

    Section 7: Implementing AI in Your Organization

    Lecture 22 Choosing the Right AI Security Tools

    Lecture 23 Integrating AI into Your Security Stack

    Lecture 24 Managing and Training AI Models

    Lecture 25 Measuring the ROI of AI Security

    Section 8: Summary

    Lecture 26 The End

    This course is designed for IT professionals, cybersecurity analysts, security managers, and anyone interested in understanding how Artificial Intelligence is revolutionizing the field of cybersecurity. It is ideal for learners who want a comprehensive overview of AI's current and future role in defending digital assets, without needing a deep technical background in data science.