Any discussion on cybersecurity these days will inevitably segue into AI; after all, it is the future of many modern industries.
By observing current threats and advances across the latest technology, in particular, we can make certain predictions about the new generation of cyber breaches. To be resilient in the face of such threats, cybersecurity analysts will need the versatility, speed and adaptability of AI.
Sophisticated hacking tools are becoming widespread; breaching business networks and systems no longer require the expertise and experience it once did. For cybersecurity, this means an increase in both attacks and uncertainty of where, why and when for a range of actors.
From governments to SMEs and everyday individuals, we’re all at risk of highly damaging cyber attacks.
Approaching cybersecurity from a reactive and defensive manner is already an outdated and dangerous way to operate. With AI capabilities, cybersecurity systems and analysts now have the power to detect threats in real-time and even predict attacks before they happen.
AI’s superpower lies in its ability to analyse large quantities of data at lightning speed and perform advanced risk modelling in a way manual methods are ill-equipped to do.
That said, the road to wide-scale AI adoption is not an easy one. Beyond the fact that cybercriminals have access to these very same tools, small businesses are also unable to benefit from this tech, the same way bigger businesses can.
This, ultimately, poses problems across the entire business ecosystem.
Let’s dive into this in more detail.
Detecting new threats is a key area in which AI will come into play. Traditional software is unable to keep pace with the frequency at which new malware is being created. With the use of machine learning, AI can use complicated algorithms to train itself to detect malware and ransomware behaviour before it even enters a system.
By using artificial intelligence for cybersecurity, and utilising its ability to analyse vast quantities of data, analysts can identify new anomalies and cybercrime trends and build prevention strategies to counter them. More importantly, AI allows the cybersecurity industry to stay up to date in an environment that is constantly changing.
Battling bots is something that cannot be done with manual responses alone. Artificial Intelligence and machine learning can help systems distinguish between search engine crawlers (good bots), bad bots and humans. This will be a valuable resource given the fact that bots make up a good portion of internet traffic today.
Breach risk prediction is another way analysts and systems can use Artificial Intelligence for cybersecurity. By monitoring an IT asset inventory, AI-based systems can determine which aspects are most vulnerable to a breach and allocate resources where necessary. The prescriptive insights offered by AI systems can help organisations enforce their cyber resilience by optimising configurations, controls and processes.
Better endpoint protection is another benefit as traditional signature protection has its limitations when put up against new malware and an ever-increasing number of devices that work remotely. AI-driven endpoint protection can establish baseline behaviour for any given endpoint and then flag and take action if any irregular activity occurs.
Artificial intelligence is a versatile tool that can be used on both ends of the spectrum. This means that as much as it can support our cybersecurity needs, it can also prove to be the cause of significant disruptions.
Equipped with AI capabilities, hackers can attack entire networks at a much faster rate. With it, they also gain the ability to manipulate surveillance systems and analyse mass-collected data, which can prove to be a destructive tool when it comes to manipulating social opinions and political views.
Moreover, acquiring the necessary data sets to train an AI system requires time and resources, making it hard for smaller organisations to use this technology. This will make them easy targets for hackers equipped with AI and a great place for aspiring cybercriminals to test and hone their skills.
What’s more, larger organisations will need to make more substantial investments to make the most of an AI-based cybersecurity system. Without proper access to the necessary data, it is possible that AI systems can yield false positives and inaccurate results inadvertently rendering them useless and these systems vulnerable to attacks.
The biggest potential threat posed by AI, however, is its ability to learn and make decisions. Once hacked, the hacker will not have to provide any further instructions; the threat just becomes harder to identify and even harder to stop.
If harnessed ethically and accurately, AI can shift the tide from cyber threats in favour of cybersecurity.
Over time, as more research and development is conducted and the technology becomes more widespread, it will become more affordable and accessible, allowing more organisations access to more powerful, AI-driven cybersecurity systems.
The biggest benefit, however, will be the change in approach it will introduce to the cybersecurity ecosystem. Analysts will be able to predict threats and vulnerabilities more accurately and allocate the necessary resources while responses can be near-instant in the face of an attack.
AI will level the playing field, eliminating the inefficiencies of manual operations and introducing highly sophisticated autonomous responses.
Cybersecurity can finally take a predictive stance as opposed to a reactive one.
