The Biden Administration and Western allies have formally accused the Chinese government of being behind a massive cyberattack on Microsoft email software and of working with cybercriminals on a range of other ransomware attacks and other cybercrimes. Johns Hopkins University…
Scientists have created a cybersecurity technology called Shadow Figment that is designed to lure hackers into an artificial world, then stop them from doing damage by feeding them illusory tidbits of success. The technology is aimed at protecting physical targets—infrastructure such as buildings, the electric grid, and water and sewage systems.
Attacks on vulnerable computer networks and cyber-infrastructure — often called zero-day attacks — can quickly overwhelm traditional defenses, resulting in billions of dollars of damage and requiring weeks of manual patching work to shore up the systems after the intrusion. Now, a Penn State-led team of researchers used a machine learning approach, based on a technique known as reinforcement learning, to create an adaptive cyber defense against these attacks.
The National Science Foundation has awarded a pair of professors at The University of Alabama in Huntsville (UAH), a part of the University of Alabama System, a nearly $500,000, three-year grant to develop a better way to wipe data from the solid-state drives (SSDs).
Damon McCoy and colleagues at the NYU Tandon School of Engineering analyzed multi-year data extracted from BriansClub, an underground bazaar for buying stolen and leaked credit card information. Among findings were that chip-enabled cards are no guarantee of security if owners still swipe the stripe: 85% of the stolen magnetic stripe data originated from EMV chip-enabled cards.
Instead of blocking hackers, a new cybersecurity defense approach developed by University of Texas at Dallas computer scientists actually welcomes them.
The method, called DEEP-Dig (DEcEPtion DIGging), ushers intruders into a decoy site so the computer can learn from hackers’ tactics. The information is then used to train the computer to recognize and stop future attacks.
Research from Michigan State University reveals the importance of factoring in a hacker’s motive for predicting, identifying and preventing cyberattacks.
New research from Michigan State University is the first to identify characteristics and gender-specific behaviors in kids that could lead kids to become juvenile hackers.