Finding smarter and more efficient ways of managing data overload is now dominating investment decisions in technology departments across Australia and New Zealand. With the digital universe experiencing unprecedented digital growth of roughly 40 per cent a year, data storage demand has never been more intense.
With the Internet of Things (IoT), we allow everyday objects to connect virtually to multiply the power of people, processes and machines by orders of magnitude, unleashing levels of performance never seen before.
Certainly that has value, e.g. smarter homes and buildings, better health, power reduction, improved crisis management and even increased public safety. Yet all those benefits come with associated risks: misunderstood threats to privacy and physical security, new ‘features’ that trigger unwanted and unwarranted surveillance, new attack vectors with major ripple effects and data that never ‘shuts up’, to name a few.
IoT introduces a network of networks we can't yet size, with untold breakpoints and vulnerabilities added every day. This complexity itself provides an emergent value to data that we cannot yet define. How do we protect these emergent properties? In our race to capitalise on the next big thing, we are creating the next big problem.
A large-scale network with giant-sized problems
Part of the problem is that the infrastructure of the Internet, that underpins the IoT, is designed to trust without verifying the credibility of data sources. Think about that for a moment. If all devices natively trust each other, and consequently share data, then how can we know when a device is lying? Not only that, but how can we protect a device among billions from compromise? Yielding to the unknown is dangerous in any network, but especially for a network composed of billions of nodes.
“If all devices natively trust each other, and consequently share data, then how can we know when a device is lying?”
A privacy breach in IoT could unleash brontobytes of sensitive data into the world, compromising not just privacy but also public safety. The financial liability could be in the billions.
As an industry, we need to come to terms with professional and ethical shared control of IoT. We need a universal open source model for connected devices that addresses the proprietary endpoint wireless infrastructures of today, with open standards for interface protocols, software, firmware and systems on chips and hardware, including security standards. We can’t pretend we’ve learned nothing from the cyber insecurity we already have!
So what can we do to improve security in this massive new network? Let’s start with these three things:
1.Build security and privacy into the network. IoT is a risk management game at all levels — sensors, devices, firmware, applications and data. It’s critical to build security at every point to create the IoT version of ‘defense in depth’. Where really low-powered devices are involved, it's necessary to create mechanisms for process flow security and privacy interventions.
2.Introduce analytics to make operational adjustments. In the IoT ecosystem of ecosystems, large-scale analytics will yield insights and trends regarding overall network operations, from clusters of nodes down to devices. Take advantage of these trend analyses to scan for changes and alert first responders when risks are exposed.
3.Build new, specialised systems to control the noise. Personal choice is being buried by the push for connectivity and ubiquity. Push back. Be proactive in how you manage your own privacy. Someday, there will be a market for personal supervisory control and data acquisition (SCADA) systems for controlling the noise of IoT for real people like us.
Loose lips still sink ships
We are quickly creating and adopting the future promise of IoT. We are retiring non-‘smart’ devices as a class of interim devices grows ‘smart enough’ to plug into wider networks. Infrastructure is adapting to handle the vast numbers and diversity of devices that IoT involves.
IoT presents exponential potential exposure that needs more than a multitude of linear security solutions. Tighter control, better analytics and specialised systems will help, but this is a human challenge as much as it is a technology challenge. As people, we need to demand a balance of privacy that suits our sometimes extroverted, sometimes introverted, selves. Being ‘always on’, constantly firing data into IoT, threatens more than we care to acknowledge.