Conf42 Machine Learning 2024 - Online

Virtual conference - talk title "A Beginners Guide to Adversarial Machine Learning"

We Teach CS Summit

Empowering Educators: Bringing AI Security Concepts Into the Classroom
Due to the rise of AI and Machine Learning, it is crucial to educate the next generation about using AI and Machine Learning for cybersecurity. While AI and Machine Learning have many benefits, it is important to understand these concepts in relation to cybersecurity because systems are increasingly being targeted. Attendees will learn the best practices to ensure that AI/ML used in cybersecurity environments has been secured. In this talk, attendees will discover how AI/ML works, use cases in cybersecurity, some security concerns with AI/ML in cybersecurity, and best practices to secure machine learning and AI. Attendees will also be given an overview of useful resources that can be used to bring these concepts to the classroom.

2024 IEEE Smart Nets Conference

Presented my IEEE paper titled "End to End System Level Solution for DDoS Attack Detection and Prediction for 5G and Future Wireless Networks" during international/global conference in front of subject matter experts and researchers in academia

Day of Shecurity April 2024 (Hybrid) Sessionize Event

Hack Space Con

Talk at the international Hack Space Con conference - I spoke about attacks to the AI systems used in the space domain

ISC2 Dallas Fort Worth Chapter Meeting

How to Effectively Use AI to Solve Cybersecurity Problems

Pacific Hackers Conference Sessionize Event

Pacific Hackers Conference

Unveiling the Path to Career Success: Introducing Students to Fundamental Technology Concepts

South Africa based webinar, spoke to South African students about cybersecurity fundamentals, how to get cybersecurity careers, and how educators can introduce cybersecurity to students in rural settings with limited infrastructure

SecureWorld Midwest 2023

Introduction to Adversarial Machine Learning

SecureWorld Dallas

Talk: Introduction to Adversarial Machine Learning
With the increased reliance and use of machine learning across all industries, the attack surface in many organizations’ environments has increased. Although machine learning has many benefits, it also leads to new risks. It is crucial to understand the new security risks that machine learning brings in order to protect systems that rely on these technologies. In this presentation, attendees will learn about the different types of attacks that machine learning is vulnerable to. In addition, attendees will gain an understanding of the difference between artificial intelligence and machine learning, what adversarial machine learning is, how machine learning attacks occur, real-world case studies, and an introduction to current open-source tools offered by the industry to ensure that machine learning has been secured. By the end of the presentation, attendees will have an understanding of machine learning and its contributions to the cyber threat landscape as well as some measures they can take to increase the security of machine learning.

Bridges in Tech

Talk title: AI/ML for Cybersecurity
What you'll learn:
clear understanding of how AI/ML works within the cybersecurity landscape
Insight into the use cases of AI/ML in cybersecurity
Awareness of the security concerns associated with AI/ML in cybersecurity
Best practices to safeguard machine learning
Tips to kick-start your own AI/ML projects in cybersecurity
An overview of useful resources to deepen your knowledge