• IPG

Machine Learning Security Trends You Need To Know About In 2022

The transformative impact of machine learning tech is being felt in the IT security industry right now, enabling all sorts of improvements that benefit businesses and their customers alike.

To bring you up to speed with the latest developments in this sphere, here is a look at just a few of the trends set to gain traction in 2022.

Automation will ease the strain on organizational resources

Everything from detecting and dealing with incursion attempts to generating access control reports can now be partly or wholly automated. Machine learning is at the heart of this leap forward in IT security.

This is clearly an advantage from a business perspective since it means that organizations of all sizes can afford to monitor mission-critical systems proactively and protect against cyberattacks without needing to dedicate significant resources to this perpetual process.

It is no longer the case that only the largest and most well-funded firms can shield themselves from breaches. Machine learning security solutions are leveling the playing field and benefitting all involved while making modern tools more effective and affordable.

The other side of this coin is that cybercriminals are also turning to machine learning and big data solutions to identify targets, exploit weaknesses and subvert security systems. This is the unavoidable nature of modern IT security and one which researchers are well aware of, hence the growing role of artificial intelligence in this area.

IoT vulnerabilities will temper growth

Although the uptick in machine learning security will ensure a double digit, year-on-year increase in the value of this sector, analysts remain concerned about how the internet of things (IoT) will hamper the potential explosion in spending that might otherwise be achievable.

There has long been a debate over how IoT tech is secured with internet-enabled gadgets of all kinds creating fears that cybercriminals will put together unstoppably expansive botnets with which to execute all sorts of attacks.

Indeed this has already been achieved in the past. Manufacturers are being encouraged to improve the security of new IoT devices to avoid similar scenarios becoming more common in the future.

This is relevant from a machine learning and AI perspective because the cybersecurity arms race could become unwinnable if action is not taken to curb IoT vulnerabilities sooner rather than later. 2022 will hopefully be the year in which significant strides in the right direction are taken to shore up connected devices in the face of evolving threats.

Disruption to IT infrastructure will be more keenly felt

There is increased pressure on security researchers to implement AI and machine learning solutions in their products and services right now because businesses have never been more exposed to the financial fallout of their systems being disrupted by a cyberattack.

This is all down to the ongoing increase in remote working, fuelled by the pandemic which still grips the world. Organizations cannot afford any downtime since this will entirely quash any productivity when large portions of their workforce are reliant on telecommuting to fulfill their responsibilities.

Once again, it is the persistent, unshakable monitoring, detection and protection potential that machine learning security offers which makes it so attractive. Round-the-clock defense against the dark arts of hackers is only going to become more vital as the impact of IT disruption is amplified.

In short, machine learning and cybersecurity are set to become more closely connected in 2022 and beyond, both as a means of delivering practical benefits to businesses and to keep up with the escalating threats.

0 views0 comments

Simple. Powerful. Cybersecurity.

IPG’s GearBoxTM is the first cybersecurity tool designed to secure and protect the Internet of Things (IoT).