When it comes to security clearances, the federal government has reached a crossroads. High priority positions in areas like cybersecurity and defense are going unfilled as the security clearance ...

Juniper finds that enterprise interest in software-defined networking (SDN) is influenced by other factors, including artificial intelligence (AI) and machine learning (ML). Security challenges and ...

Walking the enormous exhibition halls at the recent RSA security conference in San Francisco, you could have easily gotten the impression that digital defense was a solved problem. Amidst branded ...

An interdisciplinary approach will be required for systems integration as many technologies are brought together including Machine Learning, SDN, Network Function Virtualization (NFV), Network Slicing ...

Why has machine learning become so vital in cybersecurity? This article answers that and explores several challenges that are inherent when applying machine learning. Machine learning (ML) is a ...

A primary goal of machine learning is to use machines to train other machines. But what happens if there’s malware or other flaws in the training data? Machine learning and AI developers are starting ...

New considerations are necessary as more businesses adopt machine learning at scale. In association withCapital One Nearly 75% of the world’s largest companies have already integrated AI and machine ...

Machine learning adoption exploded over the past decade, driven in part by the rise of cloud computing, which has made high performance computing and storage more accessible to all businesses. As ...