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 ...

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 ...

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 ...

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 ...

Artificial intelligence and machine learning cybersecurity startup Protect AI Inc. today announced the launch of Guardian, a new secure gateway that enables organizations to enforce security policies ...

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.

Nobody has ever responded to a threat they could not detect. Just ask Capital One that is facing public scrutiny over one of the largest data breaches ever: one that persisted in the company’s ...

Bottom Line: Machine learning is enabling threat analytics to deliver greater precision regarding the risk context of privileged users’ behavior, creating notifications of risky activity in real time, ...