Our contributions include classification and introduction to the relevant fields of machine learning, a comprehensive and critical overview of machine learning usage in hardware security, and an ...

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 ...

By Dr. May Wang, CTO of IoT Security at Palo Alto Networks and the Co-founder, Chief Technology Officer (CTO), and board member of Zingbox - Why has machine learning become so vital in ...

The study sheds light on the widespread use of CPS in crop management, smart greenhouses, precision irrigation, livestock ...

September 2019 [5] Davy Preuveneers and Wouter Joosen, “Sharing Machine Learning Models as Indicators of Compromise for Cyber Threat Intelligence”, 26 February 2021. [6] Rami J. Alzahrani and Ahmed ...

Interview Kickstart, a leading platform for technical interview preparation, offers an Advanced Machine Learning Course designed to equip professionals with the skills needed to excel in ML roles, ...

Surveillance has come a long way from the watchful eyes of security guards to the all-seeing lenses of today's cameras.

In cyber security, however, quantum computing offers both unprecedented capabilities and significant threats, making it a double-edged sword that demands careful navigation.

The research introduces a machine learning framework for cyber risk assessment in construction, focusing on predictive analytics and optimization techniques.

Contributor Content In 2025, integrating artificial intelligence (AI) and machine learning (ML) into cybersecurity is no longer a futuristic ideal but a functional reality. As cyberattacks grow ...