Read our article to learn more about the cybersecurity challenges AI poses.
What are the cybersecurity benefits of AI?
Artificial intelligence (AI) in threat and incident management
The many benefits. Quicker and more precise threat detection and recognition means AI can drastically reduce the impact of cyber attacks. It allows you to analyse large data volumes around the clock in real time and identify abnormal models and behaviour more quickly. Systems with AI are also able to recognise attacks before they cause any significant damage. The IBM study Global Security Operations Centre (March 2023) found that “using AI risk analysis accelerated alert classification and verification by 55% on average”.
Combining AI with automatic response technologies, organisations can address threats quicker and enable workers to react faster. This technology can also be used to automate tasks such as installing antivirus software, verifying registration keys, and updating firewall regulations—a major advantage, as this frees up time to concentrate on the core business.
AI will also be able to create user and system behaviour models to facilitate identification of suspicious activities and potential penetration attacks.
AI for data management
Data protection is crucial for companies. AI enables data to be efficiently mapped, referenced, secured, and encrypted to optimally employ them for the security process.
There are two types of measures that have to be considered to allow for development of governance and risk management tools while also allowing companies to conform with the GDPR. Firstly, technological measures including use of technologies to protect and arbitrate company IT system access and secondly organisational measures including control process for the people handling the company data, making AI a real asset in drastically boosting performance.
AI allows us to reduce the impact of cyberattacks and enhance operations efficiency while freeing up precious time and resources. We do, however, still have to ask ourselves what challenges and limitations we could be faced with when using AI, especially regarding the use of personal data.
What future challenges does AI pose for cybersecurity?
AI as a new playing field for cybercriminals
Cybercriminals employ AI to develop more sophisticated attacks capable of bypassing traditional defence systems by targeting their intended victims in a smarter and more personalised way. Generative AI, a branch of AI that revolves around autonomous content creation, can be used to generate realistic phishing e-mails or deploy malware or deepfakes. Studies have demonstrated how quickly and easily the generation of plausible malicious codes can be automated.
AI can also be leveraged for identity theft whereby facial recognition software receives corrupt data and is manipulated into processing them as authentic.
AI to limit compliance and transparency
While systems with AI can effectively detect threats, they can also create false positives or negatives that can reduce analysts’ confidence in these dedicated AI tools, throwing up questions of transparency and accountability of security.
Using AI in cybersecurity often requires access to large amounts of sensitive data which can lead to issues with data protection and compliance with legal regulations. So while automation can be useful in certain specific areas, it still seems necessary for humans to be involved in the decision-making process.
Faced with these challenges, we therefore urgently need to introduce advanced detection mechanisms such as machine learning powered anomaly detection, employ continuous monitoring technologies, and implement security technology dedicated to AI.
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