Defending Against Gen AI-Based Hacking (Gen AI Cyberseurity)

How to defend against malware, phishing, deepfakes, and other hacking/intrusion attempts that use generative content.

What you'll learn
- How to prevent hacking and attacks empowered by gen AI
- How to identify malicious, fake, and/or gen AI-created content
- How to pick and implement defense mechanisms against advanced generative threats
- How to integrate these defenses in your organization's systems and processes

Requirements
- Basic knowledge of hacking and cybersecurity is recommended, but not necessary
- Basic knowledge of what is generative AI (gen AI), and the types of content it can generate, is also recommended, but not necessary

Description
HACK YOUR LEARNING AGAINST HACKING

Cyberattacks have always been a serious threat. But, with the advent of Gen AI, we are now in a new era.

Gen AI empowers attackers to automate, accelerate and scale the execution of attacks - many of them previously manual - bypassing defenses with unprecedented sophistication.

On top of that, LLMs and deepfakes allow them to copy the writing style, likeness, voice, or more of people - or come up with synthetic entities.

In today's environment, we must not only protect against hacking, but against hacking accelerated by gen AI.

This course will teach you how to detect, prevent and mitigate cyberattacks enhanced (or executed) with gen AI.

LET ME TELL YOU… EVERYTHING.

Some people - including me - love to know what they're getting in a package.

And by this, I mean,EVERYTHINGthat is in the package.

So, here is a list ofeverything that this course covers:

You'll learn about the major avenues or channels for attack when attacks leverage gen AI, such as wired and wireless network infrastructure, endpoints of all types, system and cloud misconfigurations or identity and authentication systems, as well as the usual types of generative content used, major types of attacks that leverage it, and defenses;

You'll learn about the major attack approaches that leverage gen AI, consisting of automating or scaling elements, or producing false content of some sort, including common types such as automated vulnerability scans, producing custom or polymorphic malware, identifying and circumventing rigid rules and thresholds, or poisoning AI models and/or their training data;

You'll learn about the major defense techniques against generative AI attacks, including moving target defenses (changing elements such as IP addresses, memory locations, etc to not allow pinpointing vulnerabilities), adaptive deception (using elements like honeypots or honeytokens with dynamic components), zero-trust architectures (always requiring authentication factors for actions regardless of login status), or robustness aganst adversarial attacks or prompt injection (training models to fight malicious inputs, and/or filtering or blocking them);

You'll learn about the major defense techniques that leverage generative AI itself, such as automating vulnerability analysis (finding vulnerabilities in files with LLMs and fixing them), automating threat detection (interpreting alerts, logs and other inputs with LLMs and prioritizing them), automating patch management/version management (interpreting package vulnerabilities, CVEs, others with LLMs and prioritizing patching order, PRs, others), or automating adaptive defenses (using LLMs to automatically parse intrusion triggers and automatically change locations, ports, others);

You'll learn about the changes due to the advent of generative AI in attacks. Which defenses stay the same, which defense techniques are changed due to generative AI attacks, and which new defense types present themselves;

You'll learn about the implementation of various defenses with gen AI in the organization, such as automated vulnerability scanning in CI/CD pipelines, LLMs in ZTAs and access reviews, automating IR and security tasks, as well as the characteristics of each, best practices, and things to take into account;

You'll learn about various ethical considerations when implementing gen AI, including related to data privacy and confidentiality, transparency and explainability, accountability, and the security of the actual AI model and its pipeline;

MY INVITATION TO YOU

Remember that youalways have a 30-day money-back guarantee, so there is no risk for you.

Also, I suggest youmake use of the free preview videos to make sure the course really is a fit. I don't want you to waste your money.

If you think this course is a fit, and can take your knowledge of dealing with change to the next level… it would be a pleasure to have you as a student.

See on the other side!

Who this course is for:
- Cybersecurity/SOC professionals focusing on preventing attacks and intrusions
- Professionals of areas related to data or security that want to better protect their organization
- Any professional in an organization that wants to be better prepared against gen AI attacks
More Info