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 ...

Here are some of the ways in which machine learning has contributed to cybersecurity: 1. Malware detection: Machine learning algorithms can analyze large volumes of data to identify patterns that are ...

Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with content, and download exclusive resources. Vivek Yadav, an engineering manager from ...

SAN FRANCISCO--(BUSINESS WIRE)--RSA CONFERENCE-- Protect AI, the leading artificial intelligence (AI) and machine learning (ML) security company, today announced that it was voted Cutting Edge Machine ...

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 ...

This article was submitted in response to the call for ideas issued by the co-chairs of the National Security Commission on Artificial Intelligence, Eric Schmidt and Robert Work. It responds to ...

Machine learning has become an important component of many applications we use today. And adding machine learning capabilities to applications is becoming increasingly easy. Many ML libraries and ...

MILPITAS, Calif.--(BUSINESS WIRE)--FireEye, Inc. (NASDAQ: FEYE), the intelligence-led security company, today announced the addition of MalwareGuard™ – a new advanced machine learning based detection ...

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 ...

Malware continues to be one of the most effective attack vectors in use today, and it is often combatted with machine learning-powered security tools for intrusion detection and prevention systems.