MIT University | Breaking Cybersecurity News | The Hacker News

Are you good at hiding your feelings? No issues, your Wi-Fi router may soon be able to tell how you feel, even if you have a good poker face. A team of researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a device that can measure human inner emotional states using wireless signals. Dubbed EQ-Radio , the new device measures heartbeat, and breath to determine whether a person is happy, excited, sad, or angry. Using EQ-Radio, which emits and captures reflected radio frequency (RF) waves, the team bounced waves off a person's body to measure subtle changes in breathing patterns and heart rates. This data was then run through a bunch of algorithms and a machine-learning process programmed to match a person's behavior to how they acted previously, categorizing the person's emotion as one of the four emotional states: Pleasure, Joy, Anger and Sadness. The impressive part about the technique: EQ-Radio doesn't r

While using your cell phone at a massive public event, like a concert, conference, or sporting event, you have probably experienced slow communication, poor performance or slow browsing speeds, as crowds arrive. That's because of ' Spectrum Crunch ', which means, Interference of WiFi signals with each other. WiFi signals of all cell-phones in a large event interfere with each other because they are all fighting over the same limited spectrum but there is not enough bandwidth to handle all the traffic from the cellphones that are trying to use the same frequency slice at the same time, leaving them frustrated with painfully slow Internet access. However, a team of researchers from the MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) has developed a solution for this problem. In a new research paper, 'Real-time Distributed MIMO Systems,' published online this week, the MIT team described a system for managing networks that cause the WiFi

Identities now transcend human boundaries. Within each line of code and every API call lies a non-human identity. These entities act as programmatic access keys, enabling authentication and facilitating interactions among systems and services, which are essential for every API call, database query, or storage account access. As we depend on multi-factor authentication and passwords to safeguard human identities, a pressing question arises: How do we guarantee the security and integrity of these non-human counterparts? How do we authenticate, authorize, and regulate access for entities devoid of life but crucial for the functioning of critical systems? Let's break it down. The challenge Imagine a cloud-native application as a bustling metropolis of tiny neighborhoods known as microservices, all neatly packed into containers. These microservices function akin to diligent worker bees, each diligently performing its designated task, be it processing data, verifying credentials, or

In Brief What if we could Predict when a cyber attack is going to occur before it actually happens and prevent it? Isn't it revolutionary idea for Internet Security? Security researchers at MIT have developed a new Artificial Intelligence-based cyber security platform, called ' AI2 ,' which has the ability to predict, detect, and stop 85% of Cyber Attacks with high accuracy. Cyber security is a major challenge in today's world, as government agencies, corporations and individuals have increasingly become victims of cyber attacks that are so rapidly finding new ways to threaten the Internet that it's hard for good guys to keep up with them. A group of researchers at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) are working with machine-learning startup PatternEx to develop a line of defense against such cyber threats. The team has already  developed an Artificial Intelligence system that can detect 85 percent of attacks by

Forget about Superman's X-rays vision, you can now see through walls using WI-FI device only. Scientists at MIT's Computer Science and Artificial Intelligence Lab ( CSAIL ) have developed a device that uses WiFi signals to effectively see through walls and other obstacles, and identify which persons are standing behind it. Dubbed RF Capture , the new system is enhanced version of their previous methods of capturing movements across a house – technology used by mothers to see their baby's breathing and firefighters to determine if there are survivors in a burning building. How Does RF Capture Work? The working of RF Capture is actually quite simple and relatively straightforward. RF-Capture works by transmitting wireless signals that, upon hitting a person standing behind a wall, are reflected off various body parts and then back to the device for analysis to piece together the whole image of people. RF-Capture transmits radio waves that pass thro