AI Articles and Analysis about Security

Episode Summary: Natural language processing (NLP) has become popular in the past two years as more businesses processes implement this technology in different niches. In inviting our guest today, we want to know specifically which industries, businesses or processes NLP could be leveraged to learn from activity logs.

The healthcare industry is evolving into an increasingly digital environment, and as a result cybersecurity continues to be a top priority for protecting sensitive data such as financial records and patient medical records.

Episode summary: In this episode of AI in Industry, we speak with Dr. Sanmay Das from the Washington University in St. Louis about risk prediction and management in industries like banking, insurance and finance.

AI is being likened to a "Fourth Industrial Revolution" because of it's potential for creating profound change in people’s lives, much like the invention of steam engines (First Industrial Revolution), electricity and mass production (Second Industrial Revolution), and the rise of the digital age (Third Industrial Revolution) had in the past.

The International Federation of Robotics reports that the U.S. service robot industry, which includes both industrial and domestic sectors, is a $5.2 billion market. It also estimates that home robots or domestic robots will contribute $11 billion in revenue by 2020.

Biometric solutions are typically used for security and access control across businesses and government organizations. The U.S. government has taken keen interest in biometric applications and has been aggressively funding advanced research programs in businesses that offer biometrics.

This week on AI in Industry, we explore IoT security with Bob Baxley (Chief Engineer at Bastille). This includes information on how different IoT security is compared to infosec, the unique challenges IoT security presents (for detecting and scanning wireless network traffic that runs on various protocols and for classifying types of cyberthreats), what the future of IoT security might look like, and how deep learning and machine learning tools can be used to better classify and detect threats and attacks in the cyberspace.

This article was written in partnership and collaboration with the IEEE. For more information about content partnerships visit the Emerj Partnerships page.