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AI in Cybersecurity: Securing Tomorrow Today

Written by Kamal Nagpal, Senior Director – Middle East, Cloud and Network Services, Nokia

As the digital world grows more complex and hostile, the imperative to keep us safe falls on the cybersecurity and telecom industry. Cybersecurity needs to be proactive and not just reactive. In this regard, Artificial Intelligence (AI) and Machine Learning (ML) have quietly revolutionised how we defend against cyber threats. AI’s innate ability to act, learn, and predict is what embeds it so deeply in cybersecurity.

While countries like the UAE make significant strides in adapting AI into every aspect of nation-building with new measures like the AI Blueprint, creating a system on which progress can be made and one that remains safe and vigilant to external threats is essential and central to all communication service providers.

AI: The Past and Present
Predicting an attack before it happens has always been, in essence, what we do as cybersecurity professionals. AI and Machine Learning (ML) are not new entrants and have been around since before generative AI took the stage. The early 2000s saw the first machine learning systems that were employed to identify and mitigate spam mail. As the threats grew more complex, so did the technologies, going from simple rule-based systems to advanced algorithms capable of predictive analysis and real-time threat detection.

Malicious actors continue to grow and use more sophisticated ransomware. Communication Service Providers across the board increasingly struggle to keep up with the ever-changing nature of threat vectors and 42% of CSP respondents believe that fragmented security tools make it harder for security companies to implement security capabilities across different systems. Cybersecurity is of paramount importance to industries like healthcare and banking that are traditionally associated with handling vast amounts of sensitive data, and with devices on the IoT (Internet of Things).

As our reliance on smart appliances and automobiles grows, so do the threats when accessing personal data. Technology and cybersecurity experts estimate that an average data breach can cost enterprises up to US$4.2 million, and that number is only growing. The biggest threats to staying safe in the cyber world we live in are the lack of security automation, increased threat actors, increasingly sophisticated attacks, a fragmented security landscape, and stringent compliance requirements.

Is AI here to stay?
With its innately high levels of automation and insight, AI trumps traditional cybersecurity methods. Given AI’s ability to process vast amounts of data at large speeds, it can also leverage machine learning algorithms to identify patterns and anomalies that can help mitigate threats in a timeframe that cannot be matched by human operators. Perhaps, one of the greatest contributions of AI and machine learning is its ability to analyze behavior. As it continues to gather and analyze threat information from diverse sources, it provides a sharper and more nuanced defence mechanism. The foresight that AI provides enables organizations to implement preventive measures rather than reactive responses, shifting the paradigm of cybersecurity from defence to prevention.

This isn’t to say that there are no challenges when it comes to leveraging AI and machine learning for cybersecurity. Ensuring that the technology operates within the realms of ethical use while prioritizing privacy will remain one of the greatest challenges we face. Ensuring transparency, fairness, and robustness in AI algorithms will be essential as these technologies continue to evolve.

Another omnipresent threat is that of data poisoning. Commonly regarded as one of the darker facets of the, AI can be weaponized and used to leak sensitive data, offer inaccurate information or even create malicious code. Ensuring a robust data validation process to filter out poisoned data and continuous monitoring through risk assessment is imperative to keep AI models safe for a digitally secure future.

The future success of AI is dependent on continuing to have regulatory environments that enable the use of AI across industries and avoiding a fragmented approach that may hinder its adoption. Regional and global collaboration is also an important aspect of staying safe. Sharing threat intelligence and best practices across borders can enhance the overall security of the region.

The use of AI in cybersecurity is more than just a passing trend. Its future is certainly enmeshed with the future of AI, and if we were to look ahead with the data available today, AI could soon be one of the cornerstones of modern and future cybersecurity strategies. As we stand on the brink of new technological frontiers, can we afford not to invest in AI-driven cybersecurity?

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