CYBERSECURITY OF CLOUD, BIG DATA AND AI
SERGEY GORDEYCHIK
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Combinatorics and graph theory lay at the heart of discrete mathematics and computer science. In the course, we begin with a brief review of the fundamentals of combinatorics---counting, permutations, binomial coefficients, and the pigeonhole principle---and then devote most of the course to the fundamentals of graph theory. We cover the most common definitions and ideas of graph theory, proving important theorems and introducing important algorithms, but mostly aiming to simply establish the common language of discrete mathematics and computer science.
Sergey Gordeychik is a CIO at Inception Institute of Artificial Intelligence (Abu Dhabi, UAE), Cybersecurity programme supervisor and visiting professor of Harbour.Space University for Technology and Design (Barcelona, Spain). Before moving to IIAI, Sergey gained a wealth of practical experience in the cybersecurity industry. In particular, being Deputy CTO at Kaspersky Lab, he was responsible for establishing the vision and leading the technological development for threat intelligence, cyber threat hunting, security assessment, incident response, and vulnerability research.
As CTO at Positive Technologies, he led the development of Gartner recognized enterprise security products such as MaxPatorl, PT Application Inspector, and PT Application Firewall. Sergey used to be a director and script writer of Positive Hack Days (PHDays), the largest and most influent cybersecurity event in Eastern Europe. From 2012, he led the SCADA StrangeLove industrial cybersecurity research team and SD-WAN New Hop project.
Sergey has developed a number of training courses, including “Critical Information Infrastructure Protection”, "Wireless Networks Security" and "Security Assessment of Web Applications," published several dozens of articles on various subjects and a book called "Wireless Networks Security." He is a popular speaker on internationals security conferences such as CCC, CodeBlue, Area41, POC, Zeronighs, S4. MCSE since NT 4.0, MCT, MVP: Enterprise Security R & D, CWNA, CISSP.
He is a popular speaker on internationals security conferences such as S4, CCC, CodeBlue, Area41, POC, Zeronighs. MCSE since NT 4.0, MCT, MVP: Enterprise Security R & D, CWNA, CISSP.
The course will provide you with:
- An understanding of modern Data Centres, Cloud Platforms and AI applications components, purposes, deployments, significant drivers, and constraints
- An understanding threats and vulnerabilities in Cloud and AI Applications on different layers – from physical security to model privacy
- Practical experience in security assessment of Data Centres components
- Industrial-specific governance, risk assessment and compliance models
- Practical experience in AI specific attacks such as Adversarial ML, Model Backdooring etc.
SKILLS:
- Critical Infrastructure Protection
- Cyber Threat Hunting
- Threat Intelligence
- Industrial Cybersecurity
- Application Security
- Product Management
ABOUT SERGEY
HARBOUR.SPACE WHAT YOU WILL LEARN
DATE: 8 Jul - 26 Jul, 2019
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
HARBOUR.SPACE UNIVERSITY
RESERVE MY SPOT
DATE: 8 Jul - 26 Jul, 2019
DURATION: 3 Weeks
LECTURES: 3 Hours per day
LANGUAGE: English
LOCATION: Barcelona, Harbour.Space Campus
COURSE TYPE: Offline
All rights reserved. 2018
COURSE OUTLINECYBERSECURITY OF CLOUD, BIG DATA AND AI
BIBLIOGRAPHY
The module covers various aspects of cybersecurity and cyber resilience of modern Datacenters, Cloud and Big Data Platforms and AI Applications.
During this course we will learn cybersecurity in various aspects: from analyzing risks and the requirements of international and industry standards to vulnerability research and practical attacks against AI models such as
Adversarial ML, Model Backdooring etc.
The course is delivered by an expert who have a wealth of practical experience and member of the SCADA
StrangeLove team who has participated in dozens of security assessment and incident response projects
devoted to analysis the security of systems in various sectors of the industry.
The module covers various aspects of cybersecurity and cyber resilience of modern Datacenters, Cloud and Big Data Platforms and AI Applications.
During this course we will learn cybersecurity in various aspects: from analyzing risks and the requirements of international and industry standards to vulnerability research and practical attacks against AI models such as
Adversarial ML, Model Backdooring etc.
The course is delivered by an expert who have a wealth of practical experience and member of the SCADA
StrangeLove team who has participated in dozens of security assessment and incident response projects
devoted to analysis the security of systems in various sectors of the industry.
Session 1
AI Building Blocks
- AI development lifecycle
- Data, model, applications
- Data Centres and Cloud platforms
Session 2
Data Centre fundamentals
- Datacenter internals
- Physical security
- Support subsystems
- Building management systems
Session 4
Bare metal management
- BMC, UEFI
- Vulnerabilities of OOB interfaces
- Security of ML/GPU servers
- Supply chain management
Session 3
Network layer security
- Network segregation in DC
- Infiniband security
- Software Defined Network