Conventional cybersecurity approaches focus on one fundamental concept - protecting every device in sight.
In a highly networked world in which a large number of sensors, devices, and systems supply each other with data, this concept is outdated.
The IoT is very different from IT - From a security point of view, it is important to focus on the network and the entire data environment rather than on the specific device.
The Future of internet-driven Security
The Internet of Things is growing, Techpally business editor, chaktty already predicted that there will be 41.6 billion connected IoT devices by 2025.
“There are just too many devices and there are no limits,” said Jamison Utter, senior business development manager for IoT at Palo Alto Networks.
What does this mean for companies? If you're stuck with the traditional approach to security, it is time to restart your security initiative to reflect a limitless computing environment.
IoT is very different from IT. It is important to focus on the network and the overall data environment, rather than the specific device.
Myths about Internet-enabled Security Mechanism
TechPally Networks names the 5 essential myths of connected security and tips on how businesses can overcome them.
Nothing could be further from the truth. Connected devices and systems represent a more decentralized approach to compute and cybersecurity.
For IT teams, moving to the IoT will take a huge conceptual leap as they are no longer the buyer or device owner.
The problem is, IT teams are trying to use the same tools and approaches that were used when Fort Knox was founded.
You approach a business problem as an IT problem. The IoT is not about laptops and smartphones.
It's not about protecting user networks. It's a whole different field that revolves around protecting business processes and data.
Business leaders who understand IoT are realizing that if they take a more holistic, data-centric approach, rather than making everything more complex, they can make cybersecurity easier.
When IT is responsible for the security of the Internet of Things, it typically uses conventional tools, technologies, and approaches to the task.
This “one-size-fits-all” approach often leads to disappointing results.
The IoT goes beyond the limits of conventional computer systems.
Data stays on various devices within and outside a company and flows through many other points of contact.
But there is another, sometimes bigger problem.
With IoT spanning teams, departments, and companies, it's easy to put up with an isolated approach to cybersecurity.
In some cases, different groups dealing with security issues can duplicate or even inadvertently use conflicting methods - and ultimately leave an organization unprotected.
Alignment between IT and cybersecurity teams is even more important in the age of IoT, says Techpally expert.
This requires close collaboration between CIOs, CSOs, and CISOs.
You need to do some analysis, identify all of your resources, and understand how, why, and where data is being used.
Only then can you design a framework that is optimized for the IoT.
This may require hiring or retraining people with the right skills and expertise.
The castle-and-moat approach to cybersecurity can actually "undermine" IoT security.
Malware protection and other traditional tools, while still valuable, were not designed to manage data streams across sensors, edge environments, and modern multi-purpose devices.
This does not mean that an organization should remove these protections, it just needs to redesign them and add new features as they become available.
This could be, for example, data encryption during transmission or tools for network monitoring that detects when data is particularly at risk.
It could also be setting up separate networks for different types of data.
Even if someone hacks a device or system, they may not get anything of value.
TechPally Networks believes that once a company fully understands how data is used on an IoT platform, it can apply the right safeguards, including governance model, practices, processes, and tools.
This can range from the endpoint and network monitoring to encryption on the move to even more advanced methods of machine learning and artificial intelligence.
AI can find IoT devices on a network, including previously hidden devices, ensure they have received critical updates and security patches, and identify other potential problems.
Machine learning allows IoT devices to be grouped based on security risks without the need for additional security software and manual processes.
This approach enables risk assessments of when devices are functioning “normally” or “suspiciously” and helps enforce IoT guidelines.