In today’s digital-first world, cyber threats are evolving faster than ever. Traditional, rule-based detection tools can no longer keep pace with the sophistication of modern attacks. Organizations need a smarter, adaptive, and automated approach — this is where Machine Learning (ML)-powered anomaly detection comes in. This technology lies at the heart of next-generation Security Operations
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Introduction: The Cybersecurity Crisis for Service Providers The landscape of cybersecurity for USA Managed Service Providers (MSPs) and Managed Security Service Providers (MSSPs) in 2025 is defined by unprecedented complexity, operational frustration, and rapidly escalating threats. The “Best of Breed” tool stack, the evolution of nation-state APT groups, and the explosion in ransomware require a
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Introduction In the rapidly evolving cyber-threat landscape, traditional signature-based defences are no longer sufficient. Threat actors increasingly use stealth, lateral movement, encrypted channels, zero-day exploits and insider tactics. To keep pace, security operations centres (SOCs) need more than firewalls and rule-sets: they need systems that think, learn and adapt. Enter cognitive threat analytics – an
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