Driving Rapid and Continuous Value for IoT Through an Ecosystem Approach

Industrial IoT, IoT Security

Article | July 11, 2023

Physical and digital security are changing due to cloud-based IoT software, which makes it possible to combine them and use them to utilize data better. In almost every sector, data is essential to success, and security is no exception. To better understand what's going on in your business, you can combine cloud-based solutions that contain all the information on a single interface. For instance, integrating security camera feeds with cloud-based access control systems enables real-time visual identification verification. Utilizing cloud-based IoT technology also enhances productivity and enables quick replies. Combining digital and physical security, often known as security convergence, is another technique to optimize IoT and cloud-based security solutions. To guard against internet flaws and intrusions, a cloud-based physical security system needs cybersecurity software. In a similar vein, physical security measures prevent sensitive data from getting into the wrong hands. Teams for physical and cyber security might combine to provide a more comprehensive plan of action. Maintaining current versions of the technology you are using in your security plan is necessary for future-proofing your technology. To ensure that your cloud-based system has no vulnerabilities that could expose your company to cybersecurity risks, it is crucial to keep all software updated. Updates can be automated and carried out remotely with cloud-based software, requiring little effort on your part to keep your software current. You have the chance to develop a security system that is future-proof when a firm adopts cloud-based IoT technologies as part of your security plan. When organizations use IoT technology, cybersecurity is a significant concern. However, combining physical and digital security lets you ensure your cloud-based system is well-protected from vulnerabilities. In addition, your security and IT teams will be better able to manage the evolving security landscape if you combine physical and digital security ideas.

IoT Security

Article | October 11, 2023

Three out of four IoT projects are considered a failure, according to Cisco. This is troubling but even more so when Cisco also found 61 per cent of companies say they believe they’ve barely begun to scratch the surface of IoT can do for their business? Businesses believe in the long-term value offered by integrating IoT into their business plan, however, they lack the knowledge of what is required to ensure the success of such a complex project. By studying past failed projects, technology leaders can gain a better understanding of why they failed and what they can do differently when evaluating and undertaking new IoT initiatives.

Industrial IoT, IoT Security

Article | July 12, 2023

Manufacturers were already digitizing their processes before March 2020. The COVID-19 pandemic gave IT and operational professionals in the manufacturing space reasons to want to move faster. Teams that can’t work on the factory floor (pandemic, weather, closed roads, etc.) need a way to monitor and control processes over the network. Supply chain woes—like wildly fluctuating demand and the container ship that blocked the Suez Canal—highlighted the need for agility. A skilled labor shortage has further accelerated plans for automation. Digitization brings visibility and agility The fourth industrial revolution, also known as Industry 4.0, lays the foundation of modern digital manufacturing. It brings together cyber and physical systems, automation, industrial IoT, and better vertical and horizontal integration. The network has a starring role in digital manufacturing, connecting people and applications in any location to factory-floor assets like sensors, actuators, cameras, and industrial automation and control systems (IACS). Benefits of digitization include improved overall equipment effectiveness (OEE) uptime, product quality, worker safety, cybersecurity, 24/7 asset monitoring and faster new product introduction and accelerating plant buildouts. Four essentials for manufacturing networks As IT and operational professionals work to innovate traditional manufacturing facilities and operations, we must consider that digital manufacturing requires more networks. Here are guidelines for making sure your manufacturing network is up to the task. Use network devices specifically designed for industrial environments like factories In addition to high performance and reliability, industrial routers, switches, and firewalls need to withstand harsh environmental conditions like extreme temperatures, shock, vibration, and humidity. They also need to be able to control access, have support for real-time industrial protocols, and enable the flow of key operational data to move across applications in the cloud. Further, the operational networks they build need to be scalable and highly resilient. We designed our industrial routers and switches to meet these requirements. Give IT and OT visibility and control into what they care about The manufacturing network is a joint project of the IT and OT teams. If you’re on the IT team, you want a solution that works with your existing network management and security applications, and doesn’t require significant training or disruption. You want to automate network maintenance and quickly identify and solve performance issues, especially in this business-critical space. If you’re on the OT team, you’re probably not an IT expert. You want visibility of issues that impact availability, product quality, workforce effectiveness and straightforward recommendations to resolve them. Cisco DNA Center – proven in the largest IT networks – meets all these needs. It automates time-consuming manual tasks, continuously monitors network health, and provides reports and controls on an easy-to-use dashboard. Cisco Cyber Vision gives you visibility into assets and processes. For agile manufacturing, look for “plug-and-play” deployment Manufacturers are simultaneously expanding production, hyper-customizing products, improving operations, and launching new products and services. To achieve these goals, you need the agility to scale product capacity, change product mix, and reallocate resources as needed. Quickly shift networking and production resources where you need them using Cisco DNA Center’s plug-and-play onboarding and provisioning. Pay careful attention to cybersecurity Cybersecurity starts with knowing everything that is connected to your industrial network, who’s talking to each other and what they are saying. Cisco Cyber Vision automatically takes a complete inventory. OT teams use a graphical interface to create production zones (aka network segments) containing all assets that need to communicate. (The painting controller doesn’t need to talk to the assembly-line controller.) Cisco Identity Services Engine (ISE) deploys polices that block unintended communications between segments to keep malware infections from spreading. Cisco Cyber Vision also takes a baseline of each asset’s usual communications patterns, alerting OT and IT teams to unusual behavior that could be a sign of a security breach. Prepare to do more with less The manufacturing skills shortage has widened the skills gap, with fewer experts left on the plant floor to prevent mistakes and solve crises. Connecting your plant floor helps you do more with less. A resilient network with the four qualities I’ve described—rugged devices, IT and OT collaboration, simpler and agile network management, and cybersecurity—helps you proactively identify potential problems, discover the cause, and resolve them before they affect production or quality.

Article | April 10, 2020

As development teams race to build out AI tools, it is becoming increasingly common to train algorithms on edge devices. Federated learning, a subset of distributed machine learning, is a relatively new approach that allows companies to improve their AI tools without explicitly accessing raw user data. Conceived by Google in 2017, federated learning is a decentralized learning model through which algorithms are trained on edge devices. In regard to Google’s “on-device machine learning” approach, the search giant pushed their predictive text algorithm to Android devices, aggregated the data and sent a summary of the new knowledge back to a central server. To protect the integrity of the user data, this data was either delivered via homomorphic encryption or differential privacy, which is the practice of adding noise to the data in order to obfuscate the results.