Lifeboat Foundation

NASA selects key commercial partnerships to further its new Moon to Mars strategy.

Today, NASA announced it has selected 12 U.S. commercial companies for 19 partnerships in its crewed Moon to Mars efforts, which kicks off with a planned 2024 Artemis program crewed return to the lunar surface.

The selections entail six key areas for future development as well as a category for other exploration technologies. They are: advanced communications, navigation and avionics; entry, descent and landing; in-space manufacturing and assembly; advanced materials; power; and propulsion.

Continue reading “NASA Selects Dozen U.S. Companies For Moon To Mars Partnerships” »

A new ransomware family targeting Android devices spreads to other victims by sending text messages containing malicious links to the entire contact list found on already infected targets.

The malware dubbed Android/Filecoder. C (FileCoder) by the ESET research team which discovered it is currently targeting devices running Android 5.1 or later.

“Due to narrow targeting and flaws in both execution of the campaign and implementation of its encryption, the impact of this new ransomware is limited,” ESET’s researchers found.

Did you know that you were being scanned via that rather colorful GUI as seen from the back of the car?

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NLP.

Cell-site simulators, also known as Stingrays or IMSI catchers, are devices that masquerade as legitimate cell-phone towers, tricking phones within a certain radius into connecting to the device rather than a tower.

Cell-site simulators operate by conducting a general search of all cell phones within the device’s radius, in violation of basic constitutional protections.

Continue reading “Cell-Site Simulators/IMSI Catchers” »

Stargazing is a form of time travel.

https://www.youtube.com/watch?v=pF_rG6Tb3hc&feature=share

Don’t forget about the “Stingray Modules” in the back of every police car.

Wut?

Do you know how to jam these?

Description:

The StingRay is an IMSI-catcher, a controversial cellular phone surveillance device, manufactured by Harris Corporation.

The machine learning models that can detect our face and movements are now part of our daily lives with smartphone features like face unlocking and Animoji. However, those AI models can’t predict how we feel by looking at our face. That’s where EmoNet comes in.

Researchers from the University of Colorado and Duke University have developed the neural net that can accurately classify images in 11 emotional categories. To train the model, researchers used 2,187 videos that were clearly classified into 27 distinct emotion categories including anxiety, surprise, and sadness.