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The GNSEC AI#CYBERGUARD BOOTCAMP
– everything you need to know about AI Security.

Finally – our `AI#Cyberguard Bootcamp’ is here.
First ever. This helps you to develop a security strategy for your AI and Big Data platforms. Or to establish a security team for AI in your organization. Or to setup a risk management team for AI and machine learning. Or…. find out more…

DEMAND FOR SKILL

The rapid advancement of Artificial Intelligence (AI) and Machine Learning (ML) over the past five years has been paralleled by an evolving landscape of skill requirements, particularly within the cybersecurity domain.

The past half-decade has witnessed a shift towards the incorporation of AI/ML technologies in cybersecurity practices. This shift has been driv- en by the increasing sophistication of cyber threats, which made more advanced and adaptive countermeasures necessary. The integration of AI/ML in cybersecurity has transformed threat detection, prediction, and response strategies, making them more proactive and data-driven. Also the skill sector advanced. Academically, there has been a substantial increase in AI/ML course offerings and specialized programs aimed at equipping students with the skills needed to navigate the complexities of modern cybersecurity challenges. This includes not only graduate and postgraduate courses but also targeted short courses and certifications designed to update the knowledge base of existing professionals.
In the private sector, organizations are increasingly seeking individu- als with a blend of cybersecurity and AI/ML expertise. This demand is reflected in job postings and internal training initiatives aimed at upskilling employees. However, the rapid pace of technological advancement has led to a scenario where the demand for skilled professionals outstrips the supply, creating a noticeable skills gap.

ANALYZING SKILL GAPS

The crux of the skills gap in AI/ML and cybersecurity lies in the pace at which new threats and technologies evolve versus the speed at which individuals can be trained to address them. Traditional cybersecurity skills, while still relevant, must now be complemented with proficiency in data science, algorithmic understanding, and machine learning models. The ability to create, manage, and interpret AI-driven security systems is becoming indispensable.

The existing educational and training frameworks, although evolving, often lag behind the cutting-edge developments in AI/ML technologies. This course bridges the gap between these disciplines, equipping participants with knowledge of AI & ML security threats and vulnerabilities. We address both sides – security AND AI researcher.
This course aims to equip you with the necessary skills to become an AI Security Architect, a highly thought-after role bridging the gap between AI and cybersecurity. Embrace the continuous learning mindset, actively seek relevant resources and training opportunities, and leverage your unique strengths to bridge the gap between AI and cybersecurity.

This course empowers participants with:

  • Security Professionals: Ability to identify AI security risks, collaborate with developers, and contribute to building secure AI systems.
  • Developers: Comprehensive understanding of AI security threats, practical skills to implement defensive measures, and knowledge to collaborate effectively with security analysts.

By attending this course, both security professionals and developers gain the necessary knowledge and skills to navigate the evolving landscape of AI security.

Major Topics covered

  • AI/ML introduction – definitions and Basics
  • Machine Learning and Deep Learning
  • What skillset do I need? Math ? Phython ? Just GPT4++?
  • AI Security projects – roles and responsibilities incl. skill matrix and responsibilities
  • How AI can support the security analyst
  • How AI can support the attackers
  • Adversarial Capabilities
  • Adversarial Attacks – GAN’s and the Real World
  • Risk Scenarios/ Risk Assessments
  • and much more….

Learning Objectives

  • This course is addressing the cyber security expert in an organization.
  • After completion of the training, the participant is able to independently prepare an assessment of the cybersecurity of an AI project.
  • He/she will also be able to competently advise the responsible risk management.
  • He will be able to create an appropriate security organization (RACI) for AI projects.
  • As a developer or data scientist, he/she can effectively implement the discussed security measures and help to document the measures for future projects.

AI#CYBERGUARD BOOTCAMP

Welcome to GNSEC Academy’s AI#Cyberguard Bootcamp, a pioneering hybrid course meticulously designed for data analysts, developers, and cybersecurity professionals. This course takes you on a deep dive into the complex world of AI security, blending rigorous e-learning with interactive online sessions. Equip yourself with the skills to lead AI/ML related security projects. Develop an understanding of data-related attacks and AI vulnerabilities. Enhance your organization’s AI security posture and standards. The material is divided into more than 12.5 hours of video content, each accompanied by text and explanations, along with over 80 code examples. You will find your understanding tested by over 400 questions in the quizzes. Furthermore, the content is consistently monitored and updated to incorporate the latest significant advancements in artificial intelligence.

Content of Courses

The initial segment of the course zeroes in on the essentials, encompassing the definitions and core principles of artificial intelligence, alongside examples of current applications and fundamental models of risk and attack. Additionally, there’s a distinct section that addresses the skills needed and the organization of AI/ML projects through the lens of cybersecurity. This course serves either as an introductory pathway into the realm of AI/ML or as foundational preparation for our AI#Cyberguard Bootcamp..

  • All about AI, ML and DL
  • How much math do need? – Thoughts about skill and training
  • Tools I should to know – from Python to GPT4
  • New Cyber Risks for a new world
  • AI Security projects – roles and responsibilities incl. skill matrix and responsibilities

This course is dedicated to exploring machine learning, encompassing all key areas such as supervised, unsupervised, and reinforcement learning, each thoroughly examined through detailed examples. Rather than serving as a basic introduction to ML techniques, this module is designed as a preparatory step for our next course on attack vectors and cyber defense strategies. It also provides an in-depth analysis of Generative Adversarial Networks (GANs), offering numerous examples from a security standpoint.

  • Supervised learning in theory and praxis
  • From linear regression to decision trees
  • Unsupervised learning
  • Reinforcement learning
  • Language Models
  • Generative AI

Following broad and targeted preparatory work, this course delves into the risks and attack vectors associated with machine learning. We begin by presenting the ZoneLock model, created by GNSEC, which facilitates the depiction of security tiers across various settings. Subsequently, we explore strategies for attacking data and models, along with methods for defending against these incursions. The material is presented in great detail and supported by coding examples. Consistent with all our courses, comprehensive skill assessments are included.

  • ZoneLock(c) Security Model
  • Data Risk
  • Data Attack Vectors
  • Model Risks
  • Model Attack Vectors
  • Adversarial Capabilities and Attacks
  • Adversarial Attacks – Examples
  • Adversarial Attacks against LLM’s
  • Deep Fakes – Images, Videos,Voice
  • Cybersecurity Minimum Requirement

This course serves as a connector between contemporary AI/ML technologies and the established, robust practices of cybersecurity. It operates under the assumption that there is already a competent security infrastructure in place within the organization. The curriculum integrates the “new” threats posed by AI/ML into the framework of existing cybersecurity measures. Topics such as the AI lifecycle, threat modeling, and the creation of standard risk assessments for AI models and ML algorithms are thoroughly explored. Additionally, the course delves into AI security controls and their practical application, alongside a detailed examination of AI-focused awareness programs..

  • AI End-to-End Lifecycle
  • AI/ML Threat Modeling Taxonomy
  • AI/ML Risk Taxonomy
  • AI/ML Cyber-Security Use Cases
  • AI/ml Risk Assessment
  • AI/ML Security Controls
  • AI/ML Awareness Program

Requirements

  • Sound knowledge in Cybersecurity and Threat Intelligence
  • Good understanding of the software development process
  • Good knowledge of data analysis
  • Good understanding of complex technical matters and the will to learn new things, even if they push you to the limits

AI#Cyberguard Bootcamp by

The GNSEC Academy’s AI#Cyberguard Bootcamp is a comprehensive training course designed for data analysts, developers, and cybersecurity professionals. It focuses on AI risks, vulnerabilities, and threats in AI/ML systems, aiming to provide an in-depth understanding of both the opportunities and challenges in AI security. The course covers a range of topics, including AI and ML basics, detailed attack scenarios, risk assessments, and the development of AI/ML related security awareness programs. Targeted at professionals with a good foundation in computer science, informationsecurity, and programming skills (especially Python), the course is structured to enhance the effectiveness, efficiency, and success of AI-related cybersecurity initiatives.It prepares participants to understand and respond to various AI and ML threats, making it an essential program for those looking toadvance their careers in this rapidly evolving field.

How to attend?

Our courses are all hybrid courses – we offer an online part and an e-learning part. However, this is a very individual construct. We can do it as a full online training or as a mixed course. 90 min online in the morning, 60 mins. online at the end of the day. In-between e-learning. Or full e-learning. As you wish!!
But we can do more. We can integrate your companies security organization in our courses. Or you want us to work with already established structures in your company??

Just contact us at sales@gnsec.com.
We help you you maximize the learning experience AND your investment!!

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