Workshops

Overview of Machine Learning Tasks Supervised Learning Unsupervised Learning Reinforcement Learning Deep Learning Real-world applications of Machine Learning Lab 1: Deep Learning for face recognition Machine Learning empirical process Theoretical model of Machine Learning Application of Machine Learning in Cybersecurity Lab 2: Support Vector Machine for IoT malware threat hunting The Machine Learning Threat Model The ML attack surface Adversarial capabilities Adversarial objectives ML threat modelling Lab 3: Identifying attack surface and threat modelling of a Deep Learning agent for traffic sign detection ML training in adversarial settings ML inference in adversarial settings ML Differential Privacy and model thefts Lab 4: Data exfiltration from a trained Decision Tree model Adversarial Poisoning Attacks Adversarial poisoning attacks methodology Poisoning attacks techniques Lab 5: Poisoning attacks against a text-recognition Deep Learning agent Adversarial Evasion Attacks Adversarial evasion attacks methodology Evasion attacks techniques Lab 6: Evading an object recognition Deep Learning agent Adversarial Attacks on Malware Detection Systems Machine learning for malware analysis Poisoning and evasion attacks against ML-based malware detection systems Lab 7: Evading a deep convolutional neural network agent for malware detection ML Differential Privacy and Model Thefts Foundations of differential privacy Data inference and model theft attacks Lab 8: Stealing an overfitted machine learning model to extract credit card information Penetration Testing of ML models Penetration testing methodology of ML engines Input sanitization of ML models Payload injection attacks Lab 9: Input sanitization testing of a ML image recognition system using anomaly An adversarial learning defense reference model Detecting adversarial attacks Preventing techniques for adversarial attacks Preserving privacy ML models The ML deception Defense-in-Depth (ML-DiD) Frameworks Lab 10: architecting a defense in depth model in an AI-centered enterprise

Course Objectives At the end of the course, participants will: Understand the security threat landscape Understand the top security issues revolving around machine learning Understand how to take preventive measures Learn about the Secure Development Lifecycle (SDL) for machine learning products Gain knowledge on the security considerations when deploying production models Course Overview With the explosive growth of machine learning applications and products, the question of their security touchpoint is becoming a major interest area for many organizations. Machine learning security covers both how such products affect the security posture of the organization, and what threats they bring to such a system, as well as how to protect such systems from adversaries. This course outlines the state-of-the-art in machine learning security and how the topic has evolved. It is intended for developers and managers to make strategic decisions for their machine learning products as both a vendor and a customer. ...

Course Objectives At the end of the course, participants will: Understand the security threat landscape and how to take preventive measures Understand the top ten security issues revolving around IoT Learn about the Secure Development Lifecycle (SDL) of IoT products Learn about the dependencies and enrollment challenges of IoT products Gain knowledge on the security considerations regarding verticals of connected devices Learn from real-life examples and case studies in IoT Security Course Overview The growth and central role that the Internet of Things play in the technology world is a proven fact. IoT is bringing the network to the physical aspects of our lives; our cars, utilities, homes, cities, industries and more. With such influence, IoT security is the main concern for the whole industry of IoT stakeholders, from developers to service providers, customers, and end-users. This course outlines the state-of-the-art prevailing practices for IoT security and how this topic is evolving. It is intended for IoT developers and managers to make a strategic decision for their IoT products both as a vendor and as a customer. ...

Course Objectives At the end of the course, participants will: Understand the basic building blocks of cryptography Understand how basic blocks are used to build secure protocols Understand weaknesses and attacks against protocols Understand how cryptographic attacks are mounted through several real-life examples Learn about real-world cryptographic attacks Review current known issues in cryptography Analyse case studies of a product with failed cryptographic implementations or design decisions Understand the current stage of cryptographic building blocks and how they are affected by quantum computing Course Overview The growth and central role that the Internet of Things play in the technology world is a proven fact. IoT is bringing the network to the physical aspects of our lives; our cars, utilities, homes, cities, industries and more. With such influence, IoT security is the main concern for the whole industry of IoT stakeholders, from developers to service providers, customers, and end-users. This course outlines the state-of-the-art prevailing practices for IoT security and how this topic is evolving. It is intended for IoT developers and managers to make a strategic decision for their IoT products both as a vendor and as a customer. ...

You can find the abstract below Please Prepare for the Workshop We wIll base our workshop on an ubuntu image, which I will link below. I recommend using VirtualBox VM - which is what I use. This VM will have a basic OS, a web server and some files we would like to protect. I am also using Ubuntu as my host, with ZSH - but will explain anything that looks funny :-) ...

Some basic advice for you CV: Place a short paragraph at the top of your CV explainging what added value do you bring to a position, based on all the work experience you have so far (from all positions) Explain what did you do at each position you held and what value did you bring - not the job description Include in your CV keywords that are relevant to the position you are applying to Keep your CV clean with the most important information at the top of the page - this is your most valuable real estate on your CVs, the area with the highest chance of being read (and where decision to read further are made) In general, for most positions your academic background is not as important as you think, push it to the bottom of your CV This might merit a post by itself one day ...

A code-along workshop demonstrating an attack on bitcoin and how to exploit cryptographic weaknesses to still bitcoin