While checking with neighboring sensors is an important technique to help detect a possible breach, the security profile of the solution could be further strengthened by adding the capability to look at historical data to see if an anomalous reading has a precedent, based on, for example, weather conditions, time of year, time of day, amount of inventory, etc., that would account for the aberration.
Problem 4: “Psychotic devices”
Another dark side of IoT is what I call “psychotic devices,” IoT devices or sensors that simply go bad and start sending false readings to the system. The cause of the psychosis can be any number of issues, from the obvious, such as a software bug, a low battery, or a simple device failure, to the not so obvious, such as a construction worker inadvertently splattering a sensor with paint or covering one up with a sheet of plywood.
While psychotic devices are not an external security threat, the impact of such devices can be just as destructive. In the case of the warehouse, they could certainly bring on the ruin of the inventory inside if the precautions already mentioned in this article aren’t followed. Likewise, the approach to preventing psychotic devices from compromising an IoT environment is similar to the approach to improving security. Techniques such as comparing an anomalous reading to the output of neighboring sensors can prevent dangerous and destructive system decisions.
Many companies see IoT as an opportunity to improve their businesses. For this to become a reality, it is imperative that IoT solution providers are aware of – and are developing solutions to resolve – these dark side challenges. The moral of the story? Choose vendors carefully. Adopt a platform designed to integrate and scale. Develop common data models. Proceed with caution, implementing only the most critical scenarios first. Then build on your success.
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