Trust is a core component in platforms of all kinds, from the internet to blockchain. But IoT data calls trust into question.
We might not know it, but we face a major problem with IoT every day: trust.
For the internet, with explosion of users and the increasing numbers of malevolent agents – hackers, spammers, malware bots – make cybersecurity the number one internet-related concern for organizations.
The internet was built for human communication, via a connection protocol across the world wide web. But in IoT, machines are the users. And they are generating terabytes and petabytes of data every day.
While cybersecurity, confidentiality and privacy are prime concerns for organizations and internet users, for IoT the most important challenge is the integrity of the data it generates.
Who says IoT data is correct?
What does integrity mean in this context? Simply having assurance that data is correct and unadulterated.
As a parallel, think about a bank transaction: if you transfer €1,000 to someone, not only will the recipient confirm they have received it, but the bank uses sophisticated IT tools and logical instruments to make and record the payment. The bank is the trusted third party.
But in IoT, data is the trust of decision-making systems – and there is no human agent involved to confirm anything. In some circumstances, this could initiate false or unnecessary procedures. For example, if you put a smart thermometer under your arm and it came back with a reading of 40 degrees, you would understandably panic; however, you would feel very ill already. If you didn’t feel unwell, you would reason that the thermometer has made a mistake. But if a smart thermometer transmitted your temperature data to the cloud, it may trigger a call to the emergency services and, before you know it, an ambulance could be sent to your home.
To take another example: some cars are fitted with an SOS button in the event of a crash, and this signal can be triggered by a collision. It could also be accidentally triggered if, say, someone crashed a shopping trolley into your car at the supermarket. In this scenario, you could intervene to stop the SOS call.
But in the very near future, millions of sensors and machines will take readings of all kinds of parameters, and the ecosystems and decision-making engines they feed will take the accuracy of the data for granted. So, in an IoT ecosystem there is a need for trust to achieve data integrity.
A second element of integrity is whether to trust the algorithms in devices and ecosystems.
Testing is essential: but if there are a million devices in an IoT ecosystem, all the trillions of connections between them need to be tested.