The rollout of 5G networks has been surprisingly slow. It launched as a concept in 2016, but didn't roll out globally until 2019.
Four years later, the number of people with a 5G device is still low in most countries.
Not sure if the reason behind the slow adoption is affordability, lack of necessity, or the spread of serious misinformation about it.
One understandable criticism that can be made against 5G, however, is the potential cybersecurity risks faced by users.
The following guidance outlines the 5G cybersecurity risks users must be aware of in 2023 and how to protect against them.
The potential of 5G
When it comes to 5G networks, experts laud its advantages of high speed and low latency and all the use cases it can be applied to. Another notable advantage is that 5G is more power optimized than its predecessor and offers higher data capacity.
All of these capabilities have the potential to connect IoT devices on an unprecedented scale. This enables more homes and consumers to use faster smart devices, enabling more smart buildings such as smart homes, campuses and cities.
However, 5G networks are complex. They are designed to handle large amounts of data of different types, so complex software must be used to manage it.
Designers of 5G networks have learned that the most efficient way to automatically scale and properly handle 5G loads is through artificial intelligence and machine learning models.
Unfortunately, this approach introduces a new attack surface for bad actors.
The Attack Surface of 5G Networks
The complex software that manages 5G networks risks becoming a cybersecurity blind spot. It can be the main entry point for many bad actors. They could try to infiltrate 5G's software to hijack and manipulate the network, though that's not the only type of vulnerability or attack that consumers and carriers should be concerned about.
Because of the way 5G networks are built and operated, they will be harder to secure than previous networks. They have more attack surface and can be exploited by:
data poisoning
Machine learning algorithms allow computer systems to discern patterns, enabling them to make autonomous decisions and predictions based on the information provided.
The use of machine learning technology has been growing rapidly and the industry is expected to be close to 10 times its market size within the next seven years.
Most models are developed using sample data (also known as training data), which can be "poisoned" by cybercriminals.
Data poisoning is a form of adversarial machine learning where bad actors try to force machine learning or AI systems to make mistakes.
By introducing corrupted or inaccurate training data, they can create security blind spots that allow them to evade detection and fly under the radar.
To prevent data poisoning in machine learning models, organizations can use outlier detection techniques involving input validation, rate limiting, regression testing, manual tuning, and statistical techniques.
man-in-the-middle attack
One of the biggest advantages of 5G frequencies is that they can contain greater bandwidth than previous standards.
But this capability often comes at the cost of coverage, as data travels shorter distances on 5G networks than on 4G or 3G networks.
Network providers typically work around this limitation by installing small cells and femtocells (nodes) at different locations within a single coverage area. For example, this could be a lamp post or the side of a building.
Unfortunately, the installation of these nodes expands the number of potential attack surfaces for bad actors. If cybercriminals were to compromise any of these small cells, they could perform a so-called man-in-the-middle attack, allowing them to access network traffic and manipulate data movement.
Unfortunately, many carriers have left these devices unsecured, so they remain one of the biggest 5G cybersecurity risks in 2023.
Network providers must encrypt these nodes and the data traffic passing through them. This is the only reliable way to fight bad actors trying to launch man-in-the-middle attacks.
Exploiting Connected Device Vulnerabilities
With the influx of cheap IoT devices, many were not designed or built with security in mind.
We've already seen how low-end smart devices expose consumers to cybersecurity threats, and they could also compromise 5G networks.
As more people adopt IoT technology, it will create more points of entry and make it harder to trace the source of threat vectors.
Much of the work of mitigating these types of attacks falls on the shoulders of consumers.
Reducing the Risks of 5G Devices
Often, device users tend to procrastinate when it comes to updating their device software. These updates often feature security updates that help manufacturers protect and patch their devices against newly discovered vulnerabilities.
Therefore, consumers are strongly encouraged to ensure their 5G-connected devices are up to date.
It's also a good idea to add antivirus software or a firewall to your device's security stack, where applicable. Also, and more importantly, consumers are encouraged to buy from verified suppliers, brands, and manufacturers. While they may be slightly more expensive, this practice increases the likelihood that your device of choice will be protected against the latest attacks.
If you run a business using 5G, you must ensure that your internal network and the software that connects to it are secure. For example, local medical practices such as dental or optometry companies often rely on direct communication software to stay in touch with patients, but they must ensure that the services they use protect the privacy of patient data.
One way dental offices can keep patients and networks safe is by using dental software with security features like encryption and multi-factor authentication.
Essentially, users must think of their devices as nodes in the 5G network. Compromised devices can affect entire networks, so consumers need to stay informed and vigilant.
It's been almost five years since 5G was released, but it still feels like a relatively new technology to most people. The vast majority of the world's population does not own a 5G-capable device, so it is difficult to predict what vulnerabilities will emerge when 5G adoption reaches a tipping point.
That said, data poisoning, man-in-the-middle attacks, and exploiting vulnerabilities in connected devices are some of the ways bad actors are targeting 5G networks.
These potential threats should not deter consumers from taking advantage of the many benefits this technology offers. However, as a consumer or enterprise user of 5G, you must maintain proper network security at all times to ensure that any operator blind spots are covered.