SAP NS2’s Barry Leffew: AI, Machine Learning Could Help Agencies Outpace State-Backed Threat Actors

Barry Leffew

Barry Leffew, senior vice president and general manager of national security software at SAP National Security Services, has said agencies should leverage artificial intelligence and machine learning to counter cyber threats.

Leffew wrote that the use of AI and machine learning could provide agencies an edge against state-sponsored threat actors by helping them analyze large amounts of data, perform predictive assessments and generate actionable intelligence.

He noted that the global economic impact of state-backed threat organizations that organize complex cyber attacks could reach $8T by 2022.

Agencies could develop behavior-based cyber capabilities through the adoption of machine-learning approaches to cyber data, he said.

“Behavior-based detection observes devices through the data they’re producing and processing to detect anomalies in behavior, identifying threats before they can cripple a network, steal data or wage an attack,” Leffew added.

He called on agencies to create a continuous risk and evaluation framework designed to collect data, remediate cyber threats and predict outcomes.

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