March 3, 2022
Presented with Darktrace
Security and IT teams have been battling threats to their infrastructure and data for as long as there have been security and IT teams. But just as technology has evolved to not only support business but drive business, the bad actors have evolved, too. They seem to be in lock-step — or maybe even a step ahead at times — with even the most advanced security pros. COVID-19 forced enterprises to move to a hybrid model and a distributed workforce has only made the CISO’s job of securing endpoints more challenging.
In this report on Intelligent Security, we dive into how and why enterprises must use artificial intelligence and machine learning to thwart increasingly sophisticated attacks.
— Dan Muse, content director and managing editor
For countless companies around the world, being able to keep business going with a remote or hybrid workforce during the pandemic has been essential. While the cybersecurity challenges of having workers in the home have been massive, the use of advanced AI, machine learning and deep learning technologies in many security tools has been among the key factors in making this all possible.
Intelligent security has played an essential part in making the past two years possible for businesses.
Achieving greater visibility and control over endpoints is table stakes for any organization pursuing zero-trust security. Human and machine identities are the new security perimeter in any network, and protecting those identities with data-driven insights and intelligence is one of the highest priorities for CISOs today.
Analytics is defining the future of endpoint protection platforms and is the differentiator all vendors are looking to strengthen today.
While the initial goal of creating a business case for investing in endpoint security is to gain funding, the rigor of quantifying the costs and benefits often identifies large gaps in endpoint security coverage and security. It’s also invaluable for capturing the figure of lost endpoints, which is something few companies have a 100% visibility into today.
Machine identities’ complexity makes them a challenge to secure at scale and over their lifecycles, further complicating CISOs’ efforts to secure them as part of their zero-trust security strategies. It’s the most urgent problem many enterprises need to address, however, as just one compromised machine identity can bring an entire enterprise network down.
Relying on AI, ML, and analytics to improve endpoint visibility and control isn’t optional anymore. Bad actors and cybercriminals automating their attacks using AI and machine learning can generate thousands of attempts a second — far more than the best cybersecurity analyst teams can keep up with.
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