#6 - Cloud Security London Meetup - Attacking Containers and Machine Learning

We're back this time with a great event! We're going to be first looking at how people may attack container based workloads in the cloud, followed by a talk looking at attacks and threats against AI and Machine Learning models. We have two great speakers, all the details are below!!

When: Wednesday 3rd March 2021 - 18:00- 20:00
Location: twitch.tv/cloudsectv

Details of this event to be updated nearer the time!

Agenda
18:00-18:05 - Welcome / Intro
18:05-18:50 - Talk 1 - David Okeyode - How attackers exploit containerised workloads
18:50-19:35 - Talk 2 - Dave Walker - Risk Management and Security in Machine Learning and Data Science Environments
19:35-19:50 - Quiz / Giveaways
19:50-20:00 - Closing

Many thanks to our Sponsors for supporting this event!
Sumo Logic - https://www.sumologic.com
InfoSaaS - https://www.infosaas.com

Talk 1
How attackers exploit containerised workloads
Containers have been around for a long time. But recently, they have become commonplace within the enterprise. The Azure platform continues to extend services that we can use to host containerized applications (ACR, AKS, ACI, App Service, Function App, Batch, e.t.c). In this session, we'll be going over the Azure containerization coverage, container security threat landscape, techniques that attackers use to exploit containerized workloads.

David Okeyode - Prisma Cloud (Palo Alto)
David Okeyde is a cloud security architect at the prisma cloud speedboat at Palo Alto Networks. Before that, he was an independent consultant helping companies secure their Azure environments through private expert level trainings and assessments. He holds 13 professional certifications across Azure and AWS platforms, including the Azure Security Engineer, Azure DevOps and AWS Security Specialist certifications. He has also authored two cloud computing courses for the popular cybersecurity training platform - Cybrary.

David has over a decade of experience in Cybersecurity (consultancy, design, implementation) and over 6 years of experience as a trainer. He has worked with organizations of different sizes from startups to major enterprises to government organizations.

David has developed multiple vulnerable by design automation templates that can be used to practice cloud penetration testing techniques.

Talk 2
Risk Management and Security in Machine Learning and Data Science Environments - Dave Walker
While ML environments typically require controls to implement Confidentiality, Integrity and Availability like any other kind of workload, the threat landscape for ML extends and varies from those associated with more traditional systems. In this session we explore how to mitigate some of these common threats including poisoning, evasion / spoofing and fuzzing / GAN attacks, and risk of model exfiltration. We also discuss scope constraint of ML models to enhance robustness, and means of making hybrid systems incorporating ML models more robust against models returning incorrect results. Finally, we look into the security configurations of AWS ML service components and review implementation of key security controls including access control, network protection, and data protection.

Dave Walker - AWS
Dave helps clients to not only meet their compliance requirements, but also to characterise and assess their further threats and design and build the means of addressing them using AWS technology.

Before joining AWS, Dave worked on technical security standards and frameworks for a number of UK and US “4-letter organisations”. Originally a Security Subject Matter Expert at Sun Microsystems by way of Acorn Computers, he has been helping companies and public sector organisations to meet industry-specific and Critical National Infrastructure security requirements since 1993, and has filed patents on cloud-focussed security technologies. He has a BSc in Chemical Physics and an MSc in the Physics of Advanced Electronic Materials from the University of Bristol.