4th Industrial Revolution (4IR) - Cyber Canaries Get Out of the Mine
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The document discusses the impact of emerging technologies on various industries and society as part of the 4th Industrial Revolution (4IR). It identifies factors driving 4IR such as the Internet of Things, automation, cloud technology, 3D printing, advanced robotics, artificial intelligence, and more. The document summarizes how these technologies are already changing how people work, travel, buy goods, and live. It also outlines new areas being developed like robotics, drones, virtual reality, and more. Finally, the document emphasizes that all industries will be disrupted and discusses skills needed to thrive in 4IR like critical thinking, collaboration, and technological literacy.
4th Industrial Revolution (4IR) - Cyber Canaries Get Out of the Mine
- 1. 4IR Cyber Canaries Get Out of the Mine philAgcaoili, CISM, CISSP, CRISC SVP, U.S. Bank SVP, Product & Security Innovation, ElavonApril 25, 2019
- 2. Never mind the gas, it was automation that got the canaries in the end. 2
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- 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
- 8. HEADING: 2030 COVFEFE 8 Source: Mymoena Ismail, NEMISA
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- 10. HEADING: 2030 COVFEFE 10 Source: Mymoena Ismail, NEMISA
- 11. HEADING: 2030 COVFEFE 11 Source: Mymoena Ismail, NEMISA
- 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
- 14. 14 Source: Andrew McAfee TEDxBoston 2012
- 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
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- 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
- 23. ALL industries and companies are being impacted by this DISRUPTION 23
- 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
- 35. Automation 35
- 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
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- 38. What tasks can be automated? I’m asking you…. 38
- 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
- 46. AI 46
- 47. Source: Kate Crawford and Vladan Joler 47
- 48. Source: Kate Crawford and Vladan Joler 48
- 49. Source: Kate Crawford and Vladan Joler 49
- 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
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- 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
Editor's Notes
- #2: FutureCon Message about the future and the basic elements that are already here
- #3: Enaex RoboMiner
- #4: 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
- #5: Electrification / sustainable energy batteries Cars Flying cars AI, ML, Data Sciences, Automation
- #6: 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
- #18: 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.
- #19: 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.
- #20: Google Wing Google Hyundai VW Amazon Uber
- #21: 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)
- #36: 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.
- #37: Recruitment will be impacted (office administration) - Algorithms are scanning resumes for desired keywords, and chat boxes arranged interviews with candidates
- #42: 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.
- #43: 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.
- #45: 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.
- #47: 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
- #49: The first part of Anatomy shows how an Amazon Echo collects data and feedback from human users.
- #50: Shows how the AI system uses interactions with customers to get smarter
- #51: internal Amazon service named Zelkova SMT solvers prove and disprove logical formulas