News

Prototype plug-in alerts drivers to vehicle cyberattacks – Thu, 16 Nov 2017
Using data-driven anomaly detection, researchers at Oak Ridge National Laboratory can tell if a hacker has modified a vehicle’s electrical signaling.

Urban Pulse maps, analyzes use of urban spaces – Wed, 08 Nov 2017
Researchers have developed open source software that maps how, when and, to a degree, by whom urban spaces are being used.

Fog mesh to the rescue when disaster strikes – Wed, 18 Oct 2017
Researchers are building a fog-enabled infrastructure that would let edge devices communicate even when there is no internet connection.

Flying cell towers could power communications in disaster areas – Wed, 27 Sep 2017
The quickly deployable communications network could deliver cell service to first responders and disaster victims.

Goosing flash for more efficient data centers – Wed, 13 Sep 2017
MIT researchers have solved flash memory’s speed problem, making it possible to reduce power consumption of data center caches by 90 percent.

Teaching drones to dogfight – Thu, 31 Aug 2017
Teams from Georgia Tech Research Institute and the Naval Postgraduate School tested the dogfighting skills of their swarms of unmanned aerial vehicles.

Using crowds to teach AI to search smarter – Wed, 16 Aug 2017
A team at the University of Texas at Austin using crowdsourced input to train its machine-learning algorithms to create a more intelligent search engine.

Using AI to monitor borders and deploy responders – Thu, 27 Jul 2017
Researchers are building a system that monitors cameras from Border Patrol ground and air vehicles and determines the most effective response to incursions.

Building a secure OS from the ground up – Thu, 06 Jul 2017
Designed by researchers as a software-defined hypervisor, S2OS will be protected from application hacks and centrally manage networking, storage and computing resources.

Using neural nets to snag malware before it strikes – Mon, 26 Jun 2017
NFrame, a hardware-based artificial neural network monitors the details of program activity at the machine level, learning how programs should execute.