IoT Slam® Live 2017: Internet of Things Conference
Security and the Internet of Things
As we rely on connected devices to make our lives better and easier, security must be considered from every aspect. All participants in the IoT ecosystem have a responsibility for the security of the devices, data and solutions. This means that device manufacturers, application developers, consumers, operators, integrators and enterprise businesses all have their part to play to follow best practices. IoT security requires a multi-layered approach. From a device point of view it should be considered at the blueprint level that starts with design and development and keeps hardware, firmware/software, and data secure through their entire life. The same approach applies if you are a security analyst or operations personnel responsible for IoT solutions. To enable the full potential of IoT, security challenges must be addressed through a combination of interoperability, education and good design—and by taking a proactive, not reactive approach to designing security features, which will result in better products and solutions.
Cognitive IoT / Artificial Intelligence
The Internet of Things is at the threshold of a tremendous opportunity. Connecting things with unique IP addresses has been possible for over a decade, but the commoditization of sensors, processors and memory now make it viable to make everyday things move beyond being just connected, but actually making them intelligent. Beyond traditional IoT implementations, cognitive computing is increasing the amount of data to improve the learning environment and increase the possibilities of what can be done with edge analytics – making sensors capable of diagnosing and adapting to their environment without the need for human intervention. Another huge advantage of cognitive IoT is the ability to combine multiple data streams that can identify patterns and give much more context than would be otherwise available.
IoT Platforms & DevOps
IoT platforms are receiving a great amount of attention as most major IoT players have rolled one out in one form or another. Platforms that have the right elements can provide tremendous value by linking the IoT endpoints to the applications and analytics needed to generate business outcomes. It’s the linchpin in a holistic IoT solution as it enables the data generated at the endpoints to be processed and meaningfully used by end users. An IoT platform must connect devices, must collect data, must handle thousands of vendors, dozens of standards and must be able to scale to millions of devices sending billions of messages. To deliver true value beyond the basics, it must add cognitive, security, privacy, insight generation and close loop automation. With these capabilities and the supporting technology advancements, the IoT platform becomes an agent of transformation for a business.
Blockchain is playing a major part in the Internet of Things by enhancing security, making transactions more seamless and creating efficiencies in the supply chain. Enterprises are leveraging blockchain in 3 key ways:
Build trust – blockchain can help build trust between the people and parties that transact together. While Person A may not know device B and may not trust it implicitly, the indelible record of transactions and data from devices stored on the blockchain provide proof and command the necessary trust for businesses and people to cooperate.
Reduce costs – IoT and blockchain can enable participants to reduce monetary and time commitment costs by ultimately removing the “middle man” from the process. Transactions and device data are now exhibited on a peer to peer basis, removing most legal or contractual costs.
Accelerate transactions – IoT and blockchain enables more transactions overall because the “middle man” is removed from the process. Smart contracts allow for organizations to reduce time needed for completing legal or contractual commitments.
Today, in a typical industrial deployment, only 1% of IoT data is actually analyzed. This is because of legacy processes and drawbacks in current IoT platforms that make it too expensive and slow to analyze the other 99% of data. Enter edge analytics. A solution that helps to address the deluge of IoT data by distributing analytics to the edge, or very close to it. Enterprises can harness the intelligence of the myriad of smart devices and their low cost computational power to allow them to run valuable analytics on the device itself. Multiple devices are usually connected to a local gateway where potentially more compute power is available, enabling more complex multi-device analytics close to the edge. Even more powerful in many cases, edge analytics are more than just operational efficiencies and scalability. Many business processes do not require complex analytics and therefore the data can be collected, processed and analyzed on the edge to drive automated decisions. Cognitive IoT can infuse these edge analytics with intelligence to make devices environmentally aware and able to react in real-time.
With increased connectivity comes several concerns. The IoT will generate immense amounts of data, which will put pressure on the Internet and force us to come up with more efficient ways to transmit and store this data. Perhaps chief among these concerns are the infrastructure considerations as other sectors grow thanks to the IoT. It's important to consider that the foundation must be well-laid to support the growing demands of a connected world.
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Organized by the Internet of Things Community
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