Securing Your AI and Machine Learning Systems

Course

Online

£ 10 VAT inc.

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Design secure AI/ML solutionsArtificial Intelligence (AI) is literally eating software as more and more solutions become ML-based. Unfortunately, these systems also have vulnerabilities; but, compared to software security, few people are really knowledgeable about this area. If it's impossible to secure AI against cyberattacks, there will be no AI-based technologies, such as self-driving cars, and yet another "AI winter" will soon be on us.This course is almost certainly the first public, online, hands-on introduction to the future perspectives of cybersecurity and adopts a clear and easy-to-follow approach. In this course, you will learn about high-level risks targeting AI/ML systems. You will design specific security tests for image recognition systems and master techniques to test against attacks. You will then learn about various categories of adversarial attacks and how to choose the right defense strategy.By the end of this course, you will be acquainted with various attacks and, more importantly, with the steps that you can take to secure your AI and machine learning systems effectively. For this course, practical experience with Python, machine learning, and deep learning frameworks is assumed, along with some basic math skills.All the code and supporting files for this course are available on GitHub at:About the Author
.
Alexander Polyakov is a cybersecurity expert and serial entrepreneur. He has over 15 years' practical experience in AI cybersecurity and other different fields, such as pentesting, security engineering, product management, architectures, and technology leadership. He is a member of Forbes Technology Council and a Forbes columnist, where he publishes his vision for the future. He has been recognized as Entrepreneur and R&D Professional of the Year by various bodies. His expertise covers cybersecurity aspects of various complex systems from enterprise applications and industry-specific systems to AI, ML, and future technologies

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Design secure AI solution architectures to cover all aspects of AI security from model to environment
Create a high-level threat model for AI solutions and choose the right priorities against various threats
Design specific security tests for image recognition systems
Test any AI system against the latest attacks with the help of simple tools
Learn the most important metrics to compare various attacks and defences
Deploy the right defence methods to protect AI systems against attacks by comparing their efficiency
Secure your AI systems with the help of practical open-source tools

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Options
  • Artificial Intelligence
  • Works
  • Approach
  • Design
  • Perspective
  • Systems
  • Technology
  • IT
  • IT Management

Course programme

Machine Learning Security 3 lectures 11:02 The Course Overview This video will give you an overview about the course. Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Introduction to Machine Learning Security - Quiz Machine Learning Security 3 lectures 11:02 The Course Overview This video will give you an overview about the course. Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Introduction to Machine Learning Security - Quiz The Course Overview This video will give you an overview about the course. The Course Overview This video will give you an overview about the course. The Course Overview This video will give you an overview about the course. The Course Overview This video will give you an overview about the course. This video will give you an overview about the course. This video will give you an overview about the course. Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Introduction to ML Security The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
The aim of this video is to introduce the problem and the ways to solve machine learning security issues.
  • Give a clear picture of artificial intelligence and machine learning
  • Provide machine learning terminologies and general classification
  • Present an overview of the machine learning attacks
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Setting Up the Environment The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
The aim of this video is to prepare the environment for further practical tasks.
  • Provide potential options to set up the environment
  • Describe the options in detail
  • Summarize all requirements
Introduction to Machine Learning Security - Quiz Introduction to Machine Learning Security - Quiz Introduction to Machine Learning Security - Quiz Introduction to Machine Learning Security - Quiz Security Test Using Adversarial Attack 5 lectures 17:40 Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable.
  • List the machine learning tasks from an attacker’s perspective
  • Describe how each machine learning task can be hacked
  • Summarize all the examples and prove the initial idea
Attacks on Classification and How They Work The aim of this video is to describe why adversarial attacks occur and how an adversarial attack works.
  • Explain why adversarial attacks take place
  • Describe what should be done to perform an attack
  • Show a step-by-step approach for attacking a machine learning model
Practical Example of Classification Attacks for MNIST Adversarial Challenge The aim of this video is to provide practical experience in attacking a machine learning model using adversarial attacks.
  • Download and configure the scripts
  • Run attack scripts against a vulnerable machine learning model
  • Experiment with different configuration values
Security test using adversarial attack - Quiz Security Test Using Adversarial Attack. 5 lectures 17:40 Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable.
  • List the machine learning tasks from an attacker’s perspective
  • Describe how each machine learning task can be hacked
  • Summarize all the examples and prove the initial idea
Attacks on Classification and How They Work The aim of this video is to describe why adversarial attacks occur and how an adversarial attack works.
  • Explain why adversarial attacks take place
  • Describe what should be done to perform an attack
  • Show a step-by-step approach for attacking a machine learning model
Practical Example of Classification Attacks for MNIST Adversarial Challenge The aim of this video is to provide practical experience in attacking a machine learning model using adversarial attacks.
  • Download and configure the scripts
  • Run attack scripts against a vulnerable machine learning model
  • Experiment with different configuration values
Security test using adversarial attack - Quiz Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Introduction to Machine Learning Tasks The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
The aim of this video is to give an overview of machine learning tasks. This is the most useful knowledge required for understanding and protecting ML solutions.
  • Introduce the rest of the machine learning tasks
  • Describe each machine learning task in detail
  • Summarize and provide the overall picture
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Attacks Against ML with Examples It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
It’s important to know how a typical attack on machine learning works and why it happens.
  • Describe why adversarial attacks exist in ML models
  • Provide a theoretical proof
  • Present an overview of machine learning attacks
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable.
  • List the machine learning tasks from an attacker’s perspective
  • Describe how each machine learning task can be hacked
  • Summarize all the examples and prove the initial idea
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable.
  • List the machine learning tasks from an attacker’s perspective
  • Describe how each machine learning task can be hacked
  • Summarize all the examples and prove the initial idea
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable.
  • List the machine learning tasks from an attacker’s perspective
  • Describe how each machine learning task can be hacked
  • Summarize all the examples and prove the initial idea
Categories of ML Tasks and Attacks The aim of this video is to demonstrate that all approaches to solving different machine learning tasks are vulnerable p...

Additional information

This course is for every ML and AI professional, engineer, or student who wants to know more about AI system security; this course will also be beneficial if you want to become more competitive and an expert. Practical experience with Python, machine learning, and deep learning frameworks is assumed, along with some basic math skills

Securing Your AI and Machine Learning Systems

£ 10 VAT inc.