AI, Machine Learning and the Need for Innovation in Cybersecurity

BY CHRIS TOWNSEND | February 11, 2019

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Despite a surge in spending on cybersecurity in recent years, federal agencies have not had the intended return on their investments. This past year, the Office of Management and Budget allocated more than $28 billion for nonclassified cybersecurity programs, compared to $7.5 billion in 2006. Those same years have seen a surge of innovation in cybersecurity, providing more sophisticated and effective tools and techniques for every stage of the cyber lifecycle.And yet a recent report from OMB found that 74 percent of federal agencies were either “at risk” or “high risk” for a cybersecurity breach. More startling, perhaps, was the finding that, in 38 percent of government cybersecurity incidents, the relevant agency could not identify how the hacker perpetrated the attack. The problem is that federal agencies are always playing catch-up. As cybersecurity technologies have evolved, so have the enterprises they were created to protect. Cloud computing and mobile devices have expanded the network in ways never believed possible. Federal agencies once only needed to defend a set perimeter, made up of hard-wired workstations in a set location. As new technologies have extended applications and data beyond the perimeter, agencies have scrambled to adapt their cyber tools, processes and policies as well.

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