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The IoT: Still feature rich, security poor
| February 11, 2019
SMARTSIDE provides Information Technology solutions for Smart Metering and Smart Grids. Using the best technologies out there, SMARTSIDE develops an innovative solution dedicated to utilities, energy services providers.
Article | March 26, 2020
Modern cars have dozens of computers on board, and they’re not just for running GPS or playing music. Computers monitor and control nearly every system on your vehicle, including steering, brakes, and the engine itself. This is why automotive cyber security is essential.
If a vehicle’s computer systems aren’t properly protected, hackers can steal data or even take control of the vehicle. As you can imagine, that makes automotive cyber security a major concern for consumers, auto companies, and OEMs alike. But what is there to know about automotive cyber security? We’ll explore what cybersecurity in the automotive industry entails and what the biggest threats are to automotive IoT and connected vehicles. We’ll also share some insights from a recent webinar by Sectigo and Mentor Graphics on how to protect connected vehicles from emerging cybersecurity threats.
AHR Expo used to be mostly a “mechanical engineering” event, and even in 2017, when I first got there, there were just a few companies who mentioned IoT or connectivity at their stands. Only the most prominent players in the HVACR industry presented their IoT solutions. In my conversations with companies at that time, no one was taking IoT very seriously. And it’s understandable, there already were Modbus, BacNet – well-defined protocols to connect machines to a PC or PLCs to make them work in unison without any Clouds and external access.
Internet of Things (IoT) devices make our lives more efficient and our day-to-day more convenient. They allow us to monitor our homes from afar, control our lights, thermostats, and locks and beef up the security of our homes—among a host of other things. But because smart devices have become so integrated into our lives, they leave us vulnerable to cybercrime too. In general, IoT devices have little to no built-in security, making them top targets for hackers. And since most IoT devices are interconnected, it puts your whole suite of devices at risk if even one gets hacked. Just as you lock your front door before you go to bed, you’ll want to make sure your IoT devices are secure before you start using them.
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.
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