CloudEXPO 2019

Hacking into IoT - How to Keep the Bad Guys Out and Let the Good Guys In

History of how we got here. What IoT devices are most vulnerable? This presentation will demonstrate where hacks are most successful, through hardware, software, firmware or the radio connected to the network. The hacking of IoT devices and systems explained in 6 basic steps.

On the other side, protecting devices continue to be a challenging effort. Product vendors/developers and customers are all responsible for improving IoT device security.

The top 10 vulnerabilities will be presented and discussed.

1. Insecure Web Interface
2. Insufficient Authentication/Authorization
3. Insecure Network Services
4. Lack of Transport Encryption/Integrity Verification
5. Privacy Concerns
6. Insecure Cloud Interface
7. Insecure Mobile Interface
8. Insufficient Security Configurability
9. Insecure Software/Firmware
10. Poor Physical Security3 things the audience will walk away with include:

1. Basic areas of vulnerability
2. Types of attacks
3. How to protect from these areas and make the systems more functional and secure.

IoT enabled Smart Mobility - Myth or Reality

Urban mobility has always been about moving people from location to location through motorized personal or public transport. However, the proliferation of sensors, smartphones and intelligent high bandwidth networks are compelling towns & cities around the world to re-think urban mobility and consider technology enablers to drive towards a vision of “smart” mobility. Furthermore, the fundamental assumptions underpinning mobility are being challenged.The Internet Of Things (IoT) has been touted as a promising technology enabler to deliver on a vision of smart mobility. We will examine the current state of IoT ecosystems, IoT enabled smart mobility efforts across the globe and help delineate the architectural considerations and cross-industry collaboration that would be essential to successfully deliver on smart mobility initiatives. A simple use case around a town/city smart mobility service will be used to illustrate our approach.

Fixing the IoIT – Internet of (Insecure) Things

The urgency behind needing to address IoT device security ASAP.

Real-World Patterns for Edge Computing

We all know that data is exploding at an unprecedented scale. This is largely being fueled by the explosive growth of the Internet of Things (IoT), currently estimated to approach 50 Billion in number by 2020. Whereas most computing devices were previously largely general purpose, when we are talking about IoT, we are talking about single-purpose vertical products that are all generating and emitting an astounding amount of data.

The recent market migration towards centralized cloud solutions has resulted in a pattern where applications are required to push their data to the cloud for processing. This is not scalable at the rate of data growth generated by the IoT. Additionally, the pattern of use of data is changing. Traditionally, data storage was expensive and deriving insight and making decisions the purview of the database or data warehouse. The advent of big data changed all that, ushering in a new era of mass data storage where decisions are now made in real-time on massive fuzzy data sets by machine learning algorithms (rather than by humans).

Even if there was enough storage in the cloud to store all the data, there is no way near enough network to transport all the data to the cloud. The advent of 5G will only increase the amount of Things creating data, while also creating a further imbalance in the network. The hop from Phone or Thing to cellular base station will be faster than the hop from cellular network to Cloud.

This new architectural shift – and what we will be covering in this session - has been termed edge computing. Rather than attempt to pull all of the data back to the cloud, it makes much more sense to process the data at the point of creation. Instead of moving the data, move the compute, harnessing the processing power and resources of all of the Things.

IoT Machine Learning at the Edge with Open Source

In this session, the speaker will explore the significant advantages of doing IoT machine learning and AI processing at the edge. This is known as "fog computing" in the IoT industry. He will walk through an example of how to package the machine learning engine and distribute it to edge processing hardware. There will also be a live demonstration of a machine learning system running in the room, all built with open source technologies that can scale.

Achieving Circular Economy in Cloud Infrastructure with Blockchain and IoT

In today's world, businesses need to implement an cloud infrastructure strategy that not only satisfies their needs to process data, store information, and serve their internal and external customers, but also manage the massive infrastructure demands on IT hardware. Using closed loop methodologies companies can enable a circular economy by eliminating costly upgrades, re-using existing IT infrastructure, and managing end-of-life or obsolete equipment in a sustainable manner. Technology megatrends such as IoT, AI, Augmented Reality, and Edge Computing can work in tandem with an IT Asset Infrastructure system that is robust but also flexible and a circular economy enables this vision.

Data at the Heart of the Cloud: Activating Data to Generate Business Outcomes

Ask yourself, “What if I knew today the true insight my data holds, what would I do differently tomorrow?” Would you change your business model from focusing on products and services to unlock experiences, outcomes, or desires? Starting with that simple question, “What if,” and then defining clear business goals and objectives, you can proactively deliver insights that help solve large business challenges.

In the end, cloud-based IoT digital transformation isn’t just a digital project, it’s a shift in culture to trust the beating heart of the cloud, the data.

Real-Time Customer Profile Architected in Cloud and Edge Infrastructure

Every enterprise today is struggling to handle the massive explosion of data that is being driven by rich customer experiences, multiple devices and IoT. These companies are spending time and money trying to build their own infrastructure to manage this data, with the goal of a unified view of their customers to drive exceptional customer experiences.

In order to create these moments that matter, enterprises need to be invest in a trusted enterprise architecture with governance controls. As the average enterprise has more than 400 different and often siloed applications, the value of unifying this data is increasingly important. But the challenge still lies in the fact that the data collected often comes with identities specific from each system, and in order to tie it together in the right way, enterprises need to ensure the data is available at the point of activation.

In this session, Sandeep will cover:

• How to best navigate a modern cloud infrastructure and edge networks, and how to leverage a heterogeneous cloud deployment of modern and open source technologies
• The architectural approach to Adobe Experience Platform’s Real-Time Customer Profile and Edge Network
• The future outlook: where things are headed and how we get there

Driverless AI

AI is a holographic projection of human consciousness, AI Will Only Be A Mirror Of Human .Authorities of decision is shifting by AI for Good.

Human and machine co-works, Reinventing the way we invent.

Is AI Recist ?

Empowering Cloud by Augmented Analytics

In this session we discuss about how Augmented Analytics Features relay on ML to produce true results that are easy to understand and Predict. How Augmented Analytics have the power to explore your data and make better decisions, faster. what actually is augmented analytics and benefits of that and how it drives business faster. we will also discuss about Smart analytics and part of smart analytics in Augmented analytics.

Using Artificial Intelligence for Evil

Artificial intelligence is positively affecting our world in previously unimaginable ways across many different industries. The use of AI is particularly interesting in the cybersecurity industry because of its unique ability to scale and prevent previously unseen zero-day attacks and for automating complicated analysis and processes at machine speed. But just in the way drug cartels built their own submarines and cellphone towers to evade law enforcement, so too will cyber-criminals build their own AI systems to carry out malicious attacks.

AI is a force for good and has demonstrated great success thus far in security applications; but AI can also be used for evil. Malcolm Harkins, Chief Security and Trust Officer at Cylance, will cover the basics of AI technology, how AI is currently being used for evil and suggested ways to combat AI attacks.

Through this session attendees will learn and understand:

• What AI is and is not, how an AI algorithm is developed.

• How AI algorithms can be undermined and how AI can be used by attackers.

• How AI is being successfully used in security and what the future may hold.