Security News

GTC Check Point Software has put Nvidia GPUs and artificial intelligence techniques to work across its broad portfolio of security tools in order to address and adapt better to an increasingly sophisticated and rapidly changing threat environment. Check Point is using AI to make life harder for those bad actors.

GTC Nvidia teased several updates to its Morpheus AI security framework at GTC this week, and also announced it would make the application framework generally available in April. In addition to releasing a pre-built version of Morpheus, Nvidia will also publish the framework's full source code on GitHub to allow developers to modify Morpheus and build security applications on top of the software.

The Italian privacy guarantor has imposed a fine of €20,000,000 on Clearview AI for implementing a biometric monitoring network in Italy without acquiring people's consent. Without ever acquiring those people's consent or informing them about the scraping of their biometric data, Clearview AI offered its clients a search service that employed artificial intelligence to match faces with identities and online activity.

Deep Instinct Threat Research team extensively monitored attack volumes and types and then extrapolated their findings to predict where the future of cybersecurity is heading, determine what motivates attackers, and most importantly, lays out the steps organizations can take now in order to protect themselves in the future. One of the most pronounced takeaways from this research on 2021 threat trends is that bad actors are becoming more successful at evading AI/ML technologies, prompting organizations to redouble efforts in the innovation race.

Security, orchestration, automation, and response platforms try to make analysts' lives easier by mapping out automated incident response playbooks that coordinate activities between security appliances. The AI comes in especially useful here given email's popularity as an attack vector.

A reporter interviews a Uyghur human-rights advocate, and uses the Otter. Ai, the automated transcription app that I had used to record the interview.

Humans have far greater difficulty identifying images of biometric spoofing attacks compared to computers performing the same task, according to research released by ID R&D. The research report finds that computers are more adept than people at accurately and quickly determining whether a photo is of an actual, live person versus a presentation attack. The study tested humans and machines by presenting them with the most common spoofing techniques: printed photos, videos, digital images, and 2D or 3D masks.

With the incorporation of artificial intelligence and machine learning tools into surveillance technologies, the definition of surveillance is changing to encompass tools that are more beneficial to the average person. Under this expanded definition, surveillance technology has far-ranging positive applications across business and retail sectors that will create safer and more enjoyable environments that benefit everyone - not just those behind the camera.

AI is not going to solve your cybersecurity problems, so can we stop pinning our hopes on it? Instead of seeking a "Magic box" to solve all our problems, organizations should be looking at how skilled personnel can work with AI to utilize the strengths of each to improve the other. Think how many possible company setups there are, applications you can run, people you can work with, economic factors that can impact a company, and so on.

Insurers' use of predictive analytics to fight fraud has reached an all-time high, according to an insurance fraud technology study by the Coalition Against Insurance Fraud and SAS. The study reveals that 80% of insurers use predictive modeling to detect fraud, up from 55% in 2018. "The shifts we've seen since the 2018 study emphasize the increasingly sophisticated technologies needed to foil insurance fraudsters' criminal exploits," said David Hartley, Director of Insurance Solutions at SAS. "Predictive modeling is up 25%. Text mining has nearly doubled, jumping from 33% to 65% in three years. These findings prove that, even as COVID-19 has fueled rampant fraud, insurers are agilely stretching their advanced analytics capabilities to counter rapidly changing threats."