AI Articles and Analysis about Security

Explore articles and reports related to artificial intelligence for security, including applications in cybersecurity, defense, fraud detection, and more.

AI for Crime Prevention and Detection - 5 Current Applications

AI for Crime Prevention and Detection – 5 Current Applications

Companies and cities all over world are experimenting with using artificial intelligence to reduce and prevent crime, and to more quickly respond to crimes in progress. The ideas behind many of these projects is that crimes are relatively predictable; it just requires being able to sort through a massive volume of data to find patterns that are useful to law enforcement. This kind of data analysis was technologically impossible a few decades ago, but the hope is that recent developments in machine learning are up to the task.

AI in Healthcare IT Security - Why Hospitals are Targets

AI in Healthcare IT Security – Why Hospitals are Targets

Episode summary: In this episode, we talk to Daniel Nigrin, MD, Senior Vice President and CIO at Boston Children’s Hospital. Daniel and I discuss why hackers have come to prey on the healthcare industry, how these hackers benefit from their illicit activities, and what healthcare IT security precautions can be taken to prevent such attacks.

Facial Recognition Applications - Security, Retail, and Beyond

Facial Recognition Applications – Security, Retail, and Beyond

Facial recognition technology has been traditionally associated with the security sector but today there is active expansion into other industries including retail, marketing and health. By 2022, the global facial recognition technology market is projected to generate an estimated $9.6 billion in revenue with a compound annual growth rate (CAGR) of 21.3 percent*.

Computer Vision for Body Language - How it Works and How it Could be Used

Computer Vision for Body Language – How it Works and How it Could be Used

As a human, we can often understand the mood, intention, and future action of another person just by looking at them. We see their posture, their facial expression, where their eyes are focused, and we can get a decent understanding of what they might do next. The problem of computer vision for body language is a much harder problem to solve, but we are indeed making progress.

AI for Cameras and Computer Vision - with Algolux's Allan Benchetrit

AI for Cameras and Computer Vision – with Algolux’s Allan Benchetrit

In the future, the vast majority of photos and videos recorded won't be seen and used by humans - they'll be seen and used by machines. This week we interview Allan Benchetrit, CEO at Algolux - a Montreal-based AI company focusing on computational imaging.

Unmanned Aerial Vehicles (UAVs) - Comparing the USA, Israel, and China

Unmanned Aerial Vehicles (UAVs) – Comparing the USA, Israel, and China

While in previous decades military unmanned aerial vehicles (UAV) were very simple pieces of equipment, the technology has advanced rapidly. They are now used all over the world and are a multi-billion dollar industry. According to the Teal Group, current worldwide military UAV production stands at around $2.8 billion, and they project it will grow to $9.4 billion in 2025.

Military Robotics Innovation

Military Robotics Innovation – Comparing the US to Other Major Powers

The market for military robotics is massive, and many developments can be observed in public competitions, university campuses, and DARPA's own announcements.

Machine Learning for Fraud Detection - Modern Applications and Risks

Machine Learning for Fraud Detection – Modern Applications and Risks

Episode Summary1: Fraud attacks have become much more sophisticated. Account takeovers are happening more often. Many security attacks involve multiple methods and unexpected attacks can devastate businesses in just a few days, as we saw with Neiman Marcus and Target. False promotion and abuse is seen not only on social media sites but is also targeted at business. To combat these risks, fraud solutions need to be smarter to keep pace with fraudsters to prevent attacks and react quickly when they do happen. This requires a fast-learning solution with the ability to continually evolve - which calls for the application machine learning for fraud detection. In this episode we talk to Kevin Lee from Sift Science and examine the shifts in the info security landscape over the past ten or fifteen year. Lee also highlights what new kinds of fraud are now possible and what machine learning solutions are available.

Security

Explore articles and reports related to artificial intelligence for security, including applications in cybersecurity, defense, fraud detection, and more.