This post was written by Jovile Bartkeviciute.
This week I had an opportunity to visit Smart IoT London conference and expo. The event was organised by CloserStill Media and was co-located with four other events: Big Data World, Cloud Security Expo, Cloud Expo Europe and Data Center World. Altogether that was 500+ talks and 500+ vendors to see in 2 days! The talks run in 28 theatres simultaneously, covering all new emerging technologies and analysing those that are industry standard already.
Here is a quick summary of the few talks that I managed to catch:
Day 1
“Trust in the 21st Century; a Blockchain Revolution” by Ian Pattison, CTO & Blockchain Leader – UK & Ireland, IBM Cloud
Key points:
- Since the early days of trading, trust was at the core of business, but with relationships spanning the globe, it is harder to track
- For 10,000 years since money was introduced, central trust authorities were “guarding the trust”
- 4 key characteristics of blockchain:
⦁ distributed, shared ledger
⦁ consensus
⦁ smart contracts
⦁ immutability - With these characteristics, blockchain can recreate person to person trust on a global scale, thus removing the central trust authorities that are in the middle
- Blockchain has the ability to remove central trust authorities by recreating person to person trust on a global scale.
“Designing IoT Experiences in the Age of Humanized Technology” by Guido Woska, Chief Client Officer – Designit
- Design is not beautification, it is all about the business transformation.
- Tech design is usually based on technology and not human-centric
- The world is a human-proof, but not human-shaped. Design must change that.
- Technology is not the driver, it is an enabler, from a desiner’s point of view, whatever you do, you need to understand that it starts with humans, then you act design and in the end you act technology
- Technology we should use it to stop/change stupid
- Make it simple – radically simple. Nobody wants to deal with the technology, but everyone wants to deal with experiences
- Less is the new more – people do not want more anymore, they often want less.
- IoT’s biggest problem is that it is not IoH (Internet of Humans)
“Transforming your business through the use of Containers, Rancher and the PaaS approach to infrastructure” by Anthony Green, Director of Cloud Computing – Interoute
Key points:
- Evolution: containers are cattle, not pets. Unlike virtual machines or physical servers that require special attention, containers usually are almost identical and have numerical names.
- The lifespan of a virtual machine is around 6x times longer than a container.
- Interoute just launched Managed Container Platform, integrating its managed global cloud infrastructure with the Rancher management platform to support enterprise digital transformation.
“A multi-layered approach for today’s threat landscape” by Andreas Meyer, Global Portfolio Manager – AT&T
Key Points:
- We are seeing the convergence of IT (information technology) and OT (operational technology) and that introduces new security challenges.
- Hackers can infect the IT side and use OT
- Today’s threat landscape needs multi-layered approach:
- Endpoint – mobile, IoT, office/fixed
- Connectivity – securing the network
- Data/Application – securing workloads/applications
“Making Data-Driven Decisions for Better DevOps Outcomes” by Andi Mann, Splunk
Key points:
- You need to make decisions using real data
- Intersection of DevOps and data
- DevOps does not start with dev and does not end with ops:
- dev is complex, ops is complex, one constant is data
- Different people can make different decisions on data, but if they do not have all data, they cannot make good decisions
- What data drives good decisions?
- Some DevOps data that might matter:
- Culture (e.g. Retention, Satisfaction, Callouts)
- Process (e.g. Idea-to-cash, MTTR, Deliver time)
- Quality (e.g. Tests passed, Tests failed, Best/worst)
- Systems (e.g. Throughput, Uptime, Build Times)
- Activity (e.g. Commits, Tests run, Releases)
- Impact (e.g. Signups, Checkouts, Revenue)
- Some DevOps data that might matter:
- It is important to use the same tools within the orgnisation, you need to make sure you are all on the same page
- We do not work in a vacuum, there are reasons for what we do that we do
- 90% of applications are opened only one time – if your application is slow to open, seconds can loose you clients
- Apply machine learning to your data
“The Cloud Impact of The Unpredictable Cybercrime” by Jesus Escolar, CEO – Exelerys
Key Points:
- The threat environment has evolved over the years, new and more damaging threats are being developed each year.
- Now, we deal with targeted attacks, advanced persistent threats and creative mobile attacks that take advantage of new vulnerabilities, social engineering, mobile proximity and cloud content.
- What’s predictable?
- Know threats of known nature
- Human: Deception, Defect, Insiders, APT
- Social: SNL, Groups, Hacktivism.
- Technical: VUL, EXP.
- Know threats of unknown nature
- Asymetric: IoT, Dark Web.
- Technical: Code, Dependencies.
- Unknown known threats
- Technical: Unpublished VUL, EXP.
- Sponsored: GOV, MIL, Agency.
- Know threats of known nature
- What is Unpredictable?
- Co-location threats
- Collaboration threats
- Collateral Threats
- Shared Networks
- Sub-contracting
- Budgets
- What vectors of cyber crime we look for?
- Threat markets: grey, black.
- Unmanaged Cloud VUL: e.g. Cloudbleed
- Agility: lack of it
- Dark Web: “who looks at the dark web for data about your company?”
- Why should we be worried?
- We can’t control what we do not know
- We can’t control non-technical items
- We can’t force business collaborations across cloud consumers
- Conclusions:
- We need to enforce shared responsibility
- Share the cloud = share the house
- Shared cyberrisk model
- Share the cloud = share the hotel
- Insurance leading to shared models
- Multi-layered, multi-service insurers
- Real cloud ORG initiatives
- We need to enforce shared responsibility
Day 2
“Live Hacking Presentation” by Sebastian Schreiber, Managing Director – SySS GmbH
Sebastian Schreiber performed different attacks on IT systems live:
- DOS attack against an internet web server
- Deactivating burglar system
- Evading antivirus
- Attacking wireless keyboards
Key point:
- It is shockingly easy to bypass protective measures in order to access sensitive information. To protect yourself, you need to look at a security world from a hackers perspective.
“GDPR, the Cloud and Brexit – Making it all work” by Ilias Chantzos, Senior Director, Symantec Government Affairs EMEA & APJ, Global CIP and Privacy Advisor – Symantec
Key points:
- There is a lot of awareness of GDPR, but not much understanding
- Before if you had a problem, you would have a problem with one country, GDPR – multijurisdictional law, all countries
- You can have security without privacy, but you cannot have privacy without security.
- Regulator does not distinguish where your data is : cloud or on-site – security need to be the same
- Rumors that it will be illegal to send data outside EU – not true, transfers outside EU are allowed, but subject to strit conditions.
- No such this as a Safe Harbor
- IP address is actually personal data
- Brexit – GDPR affects you even with Brexit; if you have any side of your business in EU, it applies to you.
“Migrating to the cloud- views from the first cloud-based bank in the UK” by Francesca Gandolfo, Chief Operations Officer – OakNorth Bank
Key Points:
- OakNorth is the first UK bank to truly move to the cloud
- They went to the cloud, not because of interest in new technologies, but because they truly believe it will bring the value to the business
- Brexit – personally a disaster, but professionally – best thing since sliced bread, since OakNorth is a UK bank for UK business.
- Cloud – cut loose from the past, break free for the future.
- Initially OakNorth went with traditional approach, but had cloud in mind from the start and designed the systems expecting to move to the cloud.
- One of the biggest challenges facing banking sector is legacy IT. By using the cloud they try to avoid building legacy.
- If you are looking to move to the cloud:
- Find a supplier you’re comfortable with
- Structure the project so that your team can proceed at pace whilst still being able to experiment.
- Don’t optimize from day one, give yourself the ability to keep on learning, evaluating and optimizing.
- This requires a mind-switch within the organization.
“Fog Computing Defined” by Angelo Corsaro, CTO – ADLINK Technology Inc.
Key Points:
- Cost of connectivity is an issue in Smart Grids as the operator as to pay for the 2G/3G/4G data-link.
- Fog computing – is similar to cloud computing, but closer to the “Things”. Like meteorological fog, it is in between the cloud and the ground. It is a horizontal system level architecture that distributes computing, storage, control and networking functions closer to the users along a cloud-to-thing continuum.
- A new infrastructure has to be “invented” for fog computing, innovating where necessary and reusing when possible.
- Fog is about reactive cyber-physical applications.
- Barcelona Smart City Platform
- MEC vs Fog computing
- 5G and MEC – focuses on real-fast, not real-time
- Real-fast and real-time – not the same
- Real-time – is all about maintaining deadlines which is essential for Fog Computing
- MEC and Fog Computing aims at the same high-level goal, which is providing a virtualised compute, storage and communication fabric, but have different constraints.
“AI is no longer for the future. For many enterprises it is for today” by Keesup Choe, CEO – Pi Ltd
Key Points:
- Having more data is not substitute for quality data
- Everybody is talking about Big Data, but regarding the business side of things, it is not big data, but wide data that gives problems.
- Wide data – high quality data that comes from a lot of different sources and not necessarily in large amounts.
- Data wrangling – removing empty fields, NaN, etc. before working with data.
- Data scientists spend 80% of their time preparing data for analysis and 76% of them say that it is the least enjoyable part of their work. This is where automation comes in.
- Automated data wrangling: machine learning element fills in incomplete data using predictive analysis.
- Data strategy – assume that you are successful and work backwards
- Use scalable languages: MATLAB or R are not the best choice, better use C++, Go – both are very scalable. The most practical one, however, is Python.
“”IOT – Show Me The Money” Over-coming Challenges & Maximising Opportunities to Drive Commercial Returns” by Erik Staaf, Managing Director – IoT as a service
Key Points:
- IoT is considered to be 4th industrial revolution
- IoT enables all aspects of the business to be digitalised in real time
- Benefits of IoT
- New business models: e.g. GE selling a service package for aircraft engines, BMW Connected car
- Cost reductions – up to 30% (e.g. TrentItalia carrying out proactive maintenance)
- Better customer experience – turning on Hive thermostat to arrive home to a nice warm home
- CRM – daily on-going relationship with the customer instead of the static annual one
- Direct relationship – taking out the middle man
- 24/7 window in the customer’s life
- Safety and Compliance – e.g. recovery from car crash (ocal)
- Asset management – where are they and how they are performing
- The IoT market will generate trillions of dollars of incremental value. Maximise your share or your competitors will do it for you. Level of disruption is not 10 years anymore – it is one year.
Overall, the talks were informative and eye opening, delivered by the industry experts explaining new technologies that could be useful for your business. With so many talks to choose from there was something for everyone – both beginners that just wished to know more about their chosen subject and people looking for tips and advice.
Apart from the talks, there were many vendors (500+), all competing for visitor’s attention with food, goodies and eye-catching stands. Here are some highlights:







