- Netscout’s approach to cybersecurity in 2025 focuses on AI-based threat intelligence, automation and real-time response to rising cyber threats
- Experts say AI is both a tool for defence and a catalyst for new attack methods, raising questions about reliance on automation and the complexity of the threat landscape
What happened: Netscout outlines AI-led cybersecurity priorities for 2025 at MWC Barcelona
At Mobile World Congress Barcelona 2025, Darren Anstee, chief technology officer for security at Netscout, outlined how the company anticipates the cybersecurity landscape will evolve this year and beyond. Netscout plans to expand the use of artificial intelligence across its security portfolio to tackle increasingly sophisticated threats, particularly for telecommunications networks and service providers.
Central to this approach is the use of AI-enabled threat intelligence systems that aggregate data from hundreds of service providers globally. According to Anstee, this creates a detailed picture of attack traffic, enabling more rapid identification of attack sources and patterns. The data is processed and delivered back to customers at frequent intervals to help them understand where attacks are coming from and potentially mitigate them more proactively.
Beyond intelligence, Netscout is integrating automation into its tools to analyse attack patterns and automate defensive adjustments. Products such as its Omnis analytics suite use machine learning to distil complex data into actionable insights, aiming to reduce the time security teams spend on manual analysis and configuration.
Anstee also emphasised the growing sophistication of distributed denial-of-service (DDoS) attacks, which increasingly combine multiple vectors and evolve during the attack itself. This makes traditional manual responses slower and less effective.
Also read: DDoS attacks on Russian apps underscore cybersecurity vulnerabilities
Also read: Does a firewall protect against DDoS attacks?
Why it’s important
The emphasis on AI and automation reflects a broader trend in cybersecurity this year. Threat actors are harnessing AI to optimise attacks, including generating more convincing phishing campaigns or adaptive DDoS strategies that shift tactics in real time. As the volume and complexity of attacks grow, traditional human-centric approaches are being stretched thin, driving demand for tools that can process and react to threats at machine speeds.
Yet this shift raises important questions. Relying heavily on AI could create new attack surfaces if the underlying models or data feed are compromised. As highlighted by industry experts, misconfigurations, biased training data, or model vulnerabilities could be exploited by adversaries. The challenge for organisations will be to balance automation with robust oversight and to ensure that human analysts retain the ability to interpret and challenge machine-generated insights.
Moreover, cybercrime is not a static field. Attackers and defenders are locked in what many analysts describe as an AI-driven arms race, where each advance in defensive capability can prompt new offensive techniques. This dynamic underscores the importance of not viewing AI as a panacea but as one component in a broader, layered defence strategy that includes traditional expertise, robust governance, and continuous monitoring.
