Whatever your thoughts on AI, it’s interesting to see how it’s being used to address the major challenges that are affecting us. Cybersecurity is just such an issue. The question is, will all of our future security upgrades harness the power of AI?
Some companies are already acting as pioneers in this field, which is giving us a glimpse into how cybersecurity will be managed in the future. Let’s explore the situation as it stands and how AI can influence that.
The Cybersecurity ‘Arms Race’
Cybersecurity is a growing issue, with large and small companies frequently becoming the target of attackers. Cyber attacks on US businesses rose by 20% from 2018 to 2,047 attacks in 2019. By 2021, the figure reported by the FBI had increased to 3,729 attacks.
Those in the field understand why the situation is frequently likened to an arms race. Whatever technologies security experts use, we can expect the hackers to do the same. That makes it a case of who can stay ahead. Adapting more quickly and the resources at hand are two key factors in the race.
How Cybersecurity Will Stay Ahead
For cybersecurity to stay ahead, it needs to be agile. That means adapting as needed, as well as innovating. Most importantly, measures need to be implemented and work quickly. That’s why AI is seen as a potential asset. The ability to automate, but also to scan and process large amounts of data in very little time, will assist agility.
Here are three ways that AI will influence existing cybersecurity practices.
Self-Sustaining Security Ecosystem
Cybersecurity is often about observing patterns to spot and respond to threats. Alongside that, it puts protective measures in place to prevent unauthorized access. When AI is applied, the machine learning aspect of the algorithm can create a self-sustaining security ecosystem.
In practice, that means software that can intelligently assess threats and use that information to improve. By incorporating self-correcting mechanisms, the AI-powered cybersecurity software can become stronger as it learns how to better protect against and spot attacks.
Detection
AI also has the potential to revolutionize threat detection. One key way will be to act proactively based on patterns to predict attacks. That can include login attempts, unusual network activity, and other anomalies.
Anything that deviates from the norm can set off alerts, and over time, it can refine its understanding of those patterns to inform security teams. In this way, even new types of attacks can be seen before or at the moment they strike.
Rectifying Vulnerabilities
Alongside detecting attacks, AI can help to identify and address system vulnerabilities. While these processes are already in place in existing systems, AI can speed up the process. As an automated task able to learn from previous attacks, it will be able to identify and classify vulnerabilities simultaneously.
A check of the identified risks can quickly be followed by the implementation of the planned solutions. Again, checks can remain in place to verify the remediation. Meanwhile, AI-powered software can continue to monitor and document the current status.
AI and Task Automation
AI’s ability to quickly scan, but also to automate tasks, has several applications when it comes to cybersecurity. Two of the most crucial elements in the future of cybersecurity and the race to stay ahead are enhancing authentication procedures and interrupting attacks. What matters most is that these tasks can be completed in seconds.
For personal protection, most individuals turn to antivirus software. However, businesses need a more comprehensive approach. Let’s take a closer look at the two ways that AI software will develop in the near future.
Enhanced Authentication
Passwords are often the weak points in systems. When harnessing the power of AI, cybersecurity systems will have enhanced authentication. While that’s partly due to 24/7 coverage, it’ll also include multifactor authentication. That means incorporating biometrics as well as continuous user verification.
Machine learning has the capabilities to analyze behavior patterns to differentiate malicious attempts from legitimate users. It can also respond quickly by adjusting access management based on the current risk level.
Interrupting Attacks
AI is also useful when it comes to improving triage of cyber attacks. It can act fast to block access. While prevention is the aim, it can also step in when defenses have been breached. For example, it can automatically apply patches.
Additionally, the fast identification of an attack can make it easier to counteract. That means the correct incident responses are identified and implemented within seconds. Another element of that is forensic evidence gathering for reporting and reducing vulnerabilities moving forward.
Final Thoughts
The more sophisticated uses of AI in cybersecurity will take some time to realize. However, there are already several benefits that machine learning can bring to the table. That’s why AI-driven solutions are likely to be central to future efforts.
