Internet of Things is all about making your appliances and devices super smart. With IoT, there are smart fridges, smart speakers as the Amazon Alexa, and there are many more with raising popularity.
The total IoT market will be worth $9 billion as we near 2020, say sources from the IoT Congress 2018. And there is massive scope for applying IoT across diverse sectors including automobiles, agriculture, health, telecom, etc.
In the global market, according to Gartner predictions, there will be over 14.2 billion things connected through the internet by 2019 end, and that the count would surge to 25 billion by 2021.
There is constant increase in interest towards IoT with a lot of challenges prevailing as well. The top most challenge is the question of privacy. There are reports claiming that use of IoT in healthcare industry could easily leave way for cybercrimes. Of course, there are privacy issues with IoT in the beginning phase. IoT involves user interaction with a hardware device. And the data gets transmitted without the need for consent of the user. This then reaches to remote servers that intercept the process. Ultimately, all these devices get connected to one remote network which when hacked or attacked can easily hit all the connected devices, say experts in IoT.
Experts suggest ways to secure real-time data sourced on IoT. This problem needs to be addressed. Software providers, device manufacturers and all app developers need to have a close watch on this issue.
Ultimately, the necessity lies with streamlined and secured data collection and transmission and storage across devices and networks so that we can devastate the likeliness of breaches. As far as the security and privacy are concerned, here are some aspects we need to look for:
- Secured IoT systems
- Constant device monitoring for any vulnerability
- Strict adherence to privacy regulations
What do experts say?
According to experts, giants like Google or Amazon need to ensure utmost data privacy, as they deal with voluminous consumer database. They say, it is possible to upkeep data privacy through contemporary technologies like machine learning. Government regulations and laws are also inevitable, they add.
As far as machine learning is concerned, it plays a crucial role. It helps the technical devices to trace human cues and eliminates the need for data transmission or recording.
When it comes to data privacy, we need to practice holistic approach. That is an ongoing process that begins at the time of designing and goes endless, for the entire lifetime involving monitoring and testing. By using penetration testing, for instance, we can zero in on the flaws in the system.