6. What is an Industrial Revolution?
When there are major changes in...
Industry
It’s usually new ways of thinking and doing and new
technologies that cause the change to happen.
TransportationEconomy Society (social structure)
The way we work, buy
and sell things
The way we travel The way we live
Source: Mymoena Ismail, NEMISA
6
7. Number of Industrial Revolutions so far? 3
And we are now starting number 4.
It is changing...
4th Industrial Revolution
The way we work, buy
and sell things
The way we travel The way we live
Source: Mymoena Ismail, NEMISA
7
12. HEADING: 2030 COVFEFE
Source: Mymoena Ismail, NEMISA
Mobile 5G / Cloud
Automation / AI
Advanced Robotics
IOT / Smart Factories
3D Printing
Energy Storage
12
13. What is Driving the 4th Industrial Revolution?
The fourth industrial revolution is the current and developing environment in which
disruptive technologies and trends are changing the way we live and work. The
factors include:
• The Internet of Things (IoT),
• Automation of Knowledge Work,
• Cloud Technology,
• 3D Printing,
• Advanced Robotics,
• Virtual Reality (VR),
• Next-Generation Genomics,
• Mobile Internet (5G networks),
• Energy Storage, and
• Artificial Intelligence (AI)
13
15. 4th Industrial Revolution
This affects social & economic sectors
Physical
Digital
Biological
What’s happening?
Different technologies are coming together
(convergence)
This is bringing different areas together
The way we work, buy
and sell things
The way we travel The way we live
Source: Mymoena Ismail, NEMISA
15
16. What is Already Happening?
Buying goods online
Paying bills online
Learning online – education
Listening to steaming music
Watching a streaming film
Playing an online game
Source: Mymoena Ismail, NEMISA
16Robotic surgery
17. What is Already Happening?
Different technologies coming together and
bringing different areas together
New products & services
with increased efficiency
(working better and faster)
for a better life
Order a taxi / ride share (Lyft) Book accommodation
17
18. What is Being Developed or New on the Market?
2017 PSB 5G Report
87% of respondents anticipate the emergence of new industries.
91% expect the invention of new products as well as services, not in existence as of yet.
85% expect the 5G connection to increase global competition among companies.
82% expect the growth of small businesses and stiffer global competition.
89% of the people surveyed expect greater productivity. 18
19. What is Being Developed or New on the Market?
Robotics
Drones
Artificial intelligence
Self
driving
cars
Virtual reality
3D printing
Internet of Things (IoT)
Bioengineering
Metadata & analytics
Digital currencies and blockchain
Quantum computing
Source: Mymoena Ismail, NEMISA
19
21. 4IR is…
• Entrepreneurial
• Innovative
• Disruptive
• Evolving at an exponential rather than a linear pace
21
22. 4IR Pluses and Minuses
Connection
Efficiency
Inability to change
Improve lives
People not ready and skilled
Not able to capture benefits
New opportunities Inequality may grow
See there are advantages and risks
Source: Mymoena Ismail, NEMISA
22
24. 4IR is Disruptive and Affects Everything
Focus on developing skills
We have to consider:
Based on partnerships across all
stakeholders.
Source: Mymoena Ismail, NEMISA
24
25. Influence curriculum
Critical thinking
Communication
Collaboration and teamwork
Complex problem solving
Creativity
Emotional intelligence
Global awareness
Financial, economic, business
and entrepreneurial literacy
Civic literacy
Health literacy
Environmental literacy
Computational thinking
Judgement and decision making
Service orientation
Negotiating
Cognitive flexibility
Influence approaches to
teaching & learning
New skills and
competencies required
Critical skills needed
Source: Mymoena Ismail, NEMISA
25
26. Understanding the systemUnderstanding the system
For over a decade, we have been talking about the
opportunities technology gives us...
A number of things were not known at the time More importantly the societal aspect was largely
missed
Today addressing youth unemployment & harnessing human innovation
forms part of the whole
to unlock effective citizen service delivery,
enhance customer experience
and bring about innovative solutions
for a better life for all
4
4
4
4
Source: Mymoena Ismail, NEMISA
26
27. The time is now to support
skills development.
27
28. Some threats and opportunities…
Some Threats and Opportunities…
Increase of mobile and
internet use comes with
own threats Cybersecurity becomes a
massive global problem.
We need the e-skills to combat this.
Also fundamental to successful digital transformation.
Source: Mymoena Ismail, NEMISA
28
31. Cybersecurity Topics to Study Now!!!
…Actually 5 years ago
• Focus on getting hands on skills and experience with the 4IR factors
• Cybersecurity Specialization Areas:
• Cloud (AWS, Azure, GCP, etc.)
• Software Development
• Agile and DevOps
• ICT, IOT, and Smart Technology (consumer and industrial)
• Blockchain
• Automation, Data Sciences, Machine Learning, and AI
• Learning to identify Risks and Cyber Consequences of 4IR
• New Vulnerabilities through the 4IR Cybersecurity Supply Chain
31
32. Refresher:
4IR Factors for Further Cybersecurity Study
• The Internet of Things (IoT),
• Automation of Knowledge Work,
• Cloud Technology,
• 3D Printing,
• Advanced Robotics,
• Virtual Reality (VR),
• Next-Generation Genomics,
• Mobile Internet (5G networks),
• Energy Storage, and
• Artificial Intelligence (AI)
32
33. Transitioning from Traditional IT to the Future of IT
Enabling capabilities in an agile, rapid, self-service fashion that empowers technology organization to focus on
delivering business capabilities faster
Changing the OrganizationTraditional IT Future of IT
As a Service Provider As a Strategic Differentiator
IT Service Operations
Manual
Processes
Self-service
Portals
Pay-per-
Use
Approval
based
Functional
Silos
SLA-driven
Automated
Processes
Integrated IT
Ops Team
Application Development
Focused on
Technology Delivery
Waterfall
Development
Focused on Business Capability
Delivery
Conventional
Delivery
Agile
Development
Continuous
Delivery
Infrastructure Management
Multiple Physical
Data Centers
Scalable and
Flexible Capacity
Hybrid Cloud
Capabilities
Legacy, On-Premise
Infrastructure
Long Provisioning
Lead Times
Fixed Data Center
Capacity
Software-Defined
Data Centers
Rapid, Automated
Provisioning
Improved time-to-market
Anticipate business needs
Greater IT financial transparency
Increased developer productivity
Attract top technology talent
Lead through innovation
Provide fast and flexible services
Scaling to match varying workloads
Service delivery orchestration
Outcomes Enabled
36. Automation
• Low-wage earners will be among the first to see their jobs
disappear, since many of their tasks are routine-based.
• Highly creative or technical positions are most likely to prevail,
along with personal care and domestic service jobs that
require interpersonal skills and emotional intelligence.
• Degrees appear to only be a partial shield against robots.
• Virtually ALL JOBS are going to begin to experience some
pressure from automation.
36
39. Software Development
39
The big takeaways for tech leaders:
Python, Ruby, and JavaScript are the most popular programming languages among software engineers.
Engineers who can code in Rust, Go, and Lua can be among the most technically proficient.
— Triplebyte, 2018
40. Software Development: Beyond “Shifting Left”
Source: Jeff Williams, Contrast Security
Five steps that greatly help:
Make developers responsible for testing
Code review quality checks
Teach testers to code
Use the same tools
Start with testability in mind
41. The first way of security: Establish security
work flow
41
Source: Jeff Williams, Contrast Security
42. The second way of security: Ensure instant
security feedback
42
Source: Jeff Williams, Contrast Security
43. The third way of security:
Build a Security Culture
• Many organizations struggle with a security culture centered on
blame, hiding, and uninformed strategy
• Key to DevSecOps culture
• Ensure that responsibility for security falls squarely on development teams
• Security experts should transform themselves into coaches and toolsmiths
• Focus for security is on teaching and automating as much as possible
• In DevSecOps, organizations strive to practice “security in sunshine”
and celebrate both vulnerabilities and attacks as a sign of good
security process and an opportunity to improve
• We are still in the early days of DevSecOps
43
Source: Jeff Williams, Contrast Security
44. Data Science and Machine Learning
A place to start: TOOLS for non-programmers
* Programming is an integral part of data science
44
45. Artificial Intelligence (AI) –
Deep Learning and its applications
• Trend Prediction
• Recognition
• New Knowledge
• Making Sense
• Replace Human
• Information retrieval (search engines)
• Pattern recognition
• Audience targeting
• Sentiment analysis (based on written
text)
• Personalization
• Automation
• Natural Language Processing
• Social media mining
• Organic search and content performance
• Brand and product differentiation
• Language Translation
• Speech Recognition
• Generating Handwriting
• Face Recognition
• Autonomous Driving
• Imitating Famous Painters
• Generating Music
• Generating Photos
*Not to be confused with AGI and ASI
45
50. AWS uses automated reasoning to achieve
security at scale
• Zelkova uses automated reasoning to analyze policies and the future consequences of
policies
• Tools include automated reasoners - Satisfiability Modulo Theories (SMT) solvers
• Zelkova has a deep understanding of the semantics of the IAM policy language and builds
upon a solid mathematical foundation
• S3 uses Zelkova to check each bucket policy and warns you if an unauthorized user is able
to read or write to your bucket
• AWS Config continuously audits AWS resource configurations and now includes Zelkova-
based managed rules such as s3-bucket-public-read-prohibited, s3-bucket-public-write-
prohibited, s3-bucket-server-side-encryption-enabled, s3-bucket-ssl-requests-only,
and lambda-function-public-access-prohibited
• AWS Trusted Advisor helps improve the security of your AWS environment, including
analyzing resource policies
• Amazon Macie uses machine learning to automatically discover, classify, and protect
sensitive data in AWS. It uses Zelkova to determine the accessibility of S3 buckets
• Amazon GuardDuty is a managed threat detection service that uses Zelkova
50
51. Mathematics for AI: Essential Math Topics
Essential lists of math topics for Machine Learning and Deep Learning:
• Linear Algebra
• Calculus
• Probability
• Optimization
https://towardsdatascience.com/mathematics-for-ai-all-the-essential-math-topics-you-need-ed1d9c910baf
https://www.quora.com/What-math-is-needed-for-artificial-intelligence-machine-learning-research-Is-it-
necessary-to-learn-everything-or-can-you-learn-just-the-specifics-such-as-matrix-multiplication
Example Cyber Activity Modeling:
Satisfiability Modulo Theories (SMT)
Semantic-Based Reasoning to Provide Meaningful Context in Human
Activity Recognizing 51
52. “Going forward, it will be important to
reinforce data gathering efforts in order
to more closely track the distributional
impacts of the current transformations.
This will make it possible to shape the
digital economy in a way that delivers
broadbased gains.”
Silja Baller, World Economic Forum
4IR Privacy
Considerations:
Data Gathering
and Aggregation
52
53. Collaboration for impact
4IR has lots of opportunities for innovation.
Innovation Opportunities
You need to have the digital skills (e-skills) to
make use of those opportunities.
You can be part of securing our future.
Source: Mymoena Ismail, NEMISA
53
55. It is not necessary to change.
Survival is not mandatory.
~W. Edwards Deming
55
56. Phil Agcaoili
Distinguished Fellow and Fellows Chairman, Ponemon Institute
Steering Committee, Financial Services –
Information Sharing & Analysis Center (FS-ISAC)
Payments Processing Information Sharing Council (PPISC)
Contributor, NIST Cybersecurity Framework
Co-Founder & Board Member, Southern CISO Security Council
Founding Member, Cloud Security Alliance (CSA)
Inventor & Co-Author
CSA Cloud Controls Matrix (ISO 27017/27018)
Security, Trust and Assurance Registry (STAR), and
CSA Open Certification Framework (OCF) – AICPA SOC 2
@hacksec
https://www.linkedin.com/in/philA
Thanks
56
Notes de l'éditeur
FutureCon
Message about the future and the basic elements that are already here
Enaex RoboMiner
1993 – Everyone should include computers (and Internet) in their work and daily life
Different – Modems, Internet, slow, apps not smart, nothing inter-connected, computing slow, Windows 95/NT
Electrification / sustainable energy batteries
Cars
Flying cars
AI, ML, Data Sciences, Automation
Change:
Waterholes
Rest stops
Gas stations
Charging stops
How does this work/compete with Ride Sharing services?
Insurance
Car ownership
Charging at home that’s smart and energy-efficient with solar
Cyber consequences of:
Always-connected
GPS-integrated
Summon
Autonomous cars, trucks, vans, and buses
https://ripple.com/insights/welcome-to-the-fourth-industrial-revolution/
Cyber-physical production systems (CPPS) is catch-all term for talking about the integration of smart, internet-connected machines and human labor. Factory managers are not simply reimagining the assembly line, but actively creating a network of machines that not only can produce more with fewer errors, but can autonomously alter their production patterns in accordance with external inputs while still retaining a high degree of efficiency.
5G can provide hundredfold increases in traffic capacity and network efficiency over 4G
It has the transformative potential on the future of connectivity worldwide
1 – 10 gigabit per second connections made to endpoints located in the field.
1000x (one-thousand fold) bandwidth for a unit area.
1ms (millisecond) end-to-end round-trip delay.
10 – 100x number of devices with connection.
Network coverage of 100%.
Availability of 99.999%.
90% decrease in energy usage by network.
As much as 10-year battery life for low power devices.
Google Wing
Google
Hyundai
VW
Amazon
Uber
The spectacular growth of IoT, Data Sciences, Machine Learning, Deep Learning,, and AI
Deep learning is a version of machine learning that uses artificial intelligence principles, such as pattern recognition or the automation of decision science to deliver actions such as driverless car driving
IoT is about sensor data collected from various devices via an HTTP protocol, to be analyzed to automate various processes (warming up your home, turning the lights on and off) and generate alerts as needed (when an oil well is about to experience big problems)
Overall, the researchers found one-quarter of jobs in the U.S. are at "high-risk" of automation
since 70 percent or more of their tasks could be done by machines.
Another 36 percent of jobs are at "medium-risk" as a machine could do between 30 and 70 percent of their tasks.
Some 40 percent of jobs are at "low-risk", with less than 30 percent of their tasks able to be performed by a robot.
Recruitment will be impacted (office administration)
- Algorithms are scanning resumes for desired keywords, and chat boxes arranged interviews with candidates
The basic cycle of DevSecOps is to identify the most critical security challenge,
implement a defense strategy,
automate security testing for that defense, and then
monitor and defend against attacks.
Both our security pipeline and the security of our software gets stronger and stronger over time.
The feedback loop shows instant feedback of both vulnerabilities and attacks to the teams that need them through the tools they are already using.
A DevSecOps pipeline is the set of tools and processes that continuously performs security work as code is written, integrated, tested, deployed, and operated.
Organizations should automate security as much as possible, and provide instant feedback to the team members that need it through the tools that they are already using.
Security feedback must be designed for consumption by developers, testers, and executives that do not have extensive security expertise.
Paxata is one of the few organizations which focus on data cleaning and preparation, and not the machine learning or statistical modeling part.
It is a Microsoft Excel-like application that is easy to use.
Auto-WEKA is an open-source data mining software that’s an easy GUI based tool for beginners in data science.
It is primarily used for educational and academic purposes for now.
DataRobot is a highly automated machine learning platform
MLBase is an open-source project.
The core idea behind it is to provide an easy solution for applying machine learning to large scale problems.
RapidMiner covers the entire life-cycle of prediction modeling, starting from data preparation to model building and finally validation and deployment.
h2o.ai Driverless AI is an enterprise-class automatic machine learning platform.
It’s available as a docker image
Very intuitive interface trains on datasets to give excellent results on par with a good solution an experienced data scientist can come up with.
Google Cloud AutoML is part of Google’s Machine Learning suite offerings that enables people with limited ML expertise to build high quality models.
Cloud AutoML Vision is built on Google’s transfer learning and neural architecture search technologies.
This tool is already being used by a lot of organizations.
Amazon Lex provides an easy-to-use console for building your own chatbot in a matter of minutes.
Powered by the same deep learning technologies as Alexa
It builds a complete Natural Language model
You can build conversational interfaces in your applications or website using Lex.
All you need to do is supply a few phrases and Amazon Lex does the rest!
It has built-in integration with the AWS
Azure ML Studio is a simple yet powerful browser based ML platform.
Democratization of AI on how AI is being deployed in some instances above
Cloud-based services opens up access to the large data sets and specialized infrastructure needed to support AI and extends the potential of the technology beyond early adopters
The first part of Anatomy shows how an Amazon Echo collects data and feedback from human users.
Shows how the AI system uses interactions with customers to get smarter
internal Amazon service named Zelkova
SMT solvers prove and disprove logical formulas