The infamous Pegasus spyware created by Israeli firm NSO can turn any infected smartphone into a remote microphone or camera. Here’s how to stay safe and know if you’ve been hacked.
THE FBI used a ‘geofence warrant’ to access data about all Android users who were near a BLM protest attack, according to new documents.
Google was served with a warrant as part of an investigation into an attempted arson at a police union building in Seattle in 2020.
The attack took place on August 24.
Researchers at the U.S. Department of Energy’s (DOE) Princeton Plasma Physics Laboratory (PPPL) have gained insight into a fundamental process found throughout the universe. They discovered that the magnetic fields threading through plasma, the charged state of matter composed of free electrons and atomic nuclei, can affect the coming together and violent snapping apart of the plasma’s magnetic field lines. This insight could help scientists predict the occurrence of coronal mass ejections, enormous burps of plasma from the sun that could threaten satellites and electrical grids on Earth.
The scientists focused on the role of guide fields, magnetic fields threading through plasma blobs, or chunks, known as plasmoids. The guide fields add rigidity to the system and ultimately affect the ratio of large plasmoids to small ones and help determine how much reconnection occurs.
Plasmoid reconnection resembles the parallel computing that occurs in smart phones or in high-powered computers that model the weather. During this computing, many processors are calculating simultaneously and making the overall calculation rate quicker. Similarly, plasmoids speed up the overall rate of reconnection by making it occur in many places at once.
After NSO, another Israeli company, QuaDream, has been caught weaponizing iPhone bugs to deploy a spyware called Reign, similar to Pegasus.
No more endless password entries.
Apple’s iOS 15.4 beta adds a long-awaited feature to unlock your phone with Face ID while wearing a face mask. The new feature works incredibly well, though it’ll still fail sometimes. But it’s much better than having to enter in your password every time.
By studying the risk of re-identification more thoroughly, researchers were able to better articulate the fundamental requirements for information to be anonymous. They realized that a robust definition of anonymous should not rely on what side information may be available to an attacker. This led to the definition of Differential Privacy in 2006 by Cynthia Dwork, then a researcher at Microsoft. It quickly became the gold standard for privacy and has been used in global technology products like Chrome, the iPhone, and Linkedin. Even the US Census used it for the 2020 census.
Differential privacy solves the problem of side information by looking at the most powerful attacker possible: an attacker who knows everything about everyone in a population except for a single individual. Let’s call her Alice. When releasing information to such an attacker, how can you protect Alice’s privacy? If you release exact aggregate information for the whole population (e.g., the average age of the population), the attacker can compute the difference between what you shared and the expected value of the aggregate with everyone but Alice. You just revealed something personal about Alice.
The only way out is to not share the exact aggregate information but add a bit of random noise to it and only share the slightly noisy aggregate information. Even for the most well-informed of attackers, differential privacy makes it impossible to deduce what value Alice contributed. Also, note that we have talked about simple insights like aggregations and averages but the same possibilities for re-identification apply to more sophisticated insights like machine learning or AI models, and the same differential privacy techniques can be used to protect privacy by adding noise when training models. Now, we have the right tools to find the optimal tradeoff: adding more noise makes it harder for a would-be attacker to re-identify Alice’s information, but at a greater loss of data fidelity for the data analyst. Fortunately, in practice, there is a natural alignment between differential privacy and statistical significance.
Although Christmas may be several weeks behind us, various colorful LED contraptions can nowadays be found in our houses at any time of year. [Tim] got his hands on an LED curtain that came with a remote control that allows the user to set not only the color of the LEDs as a whole but also to run simple animations. But these were not your standard WS2812B strips with data lines: all the LEDs were simply connected in parallel with just two wires, so how was this even possible?
[Tim] hooked up his oscilloscope to the LED strings to find out how they worked, detailing the results in a comprehensive blog post. As it turns out, the controller briefly shorts the LED strip’s supply voltage to generate data bits, similar to the way old pulse-dialing phones worked. A tiny chip integrated into each LED picks up these pulses, but retains its internal state thanks to a capacitor that keeps the chip powered when the supply line goes low.
After reverse-engineering the protocol, [Tim] went on to implement a similar design using an ATMega328P as a controller and an ATtiny10 as the LED driver. With just a few lines of code and a 100 nF buffer capacitor across the ATtiny’s power pins, [Tim] was able to turn an LED on and off by sending pulses through the supply lines. Some work still needs to be done to fully implement a protocol as used in the LED strings, but as a proof-of-concept it shows that this kind of power-line communication is possible with standard components.
What are biomarkers? They are medical signals that can measure health in an accurate and reproducible way. Common examples include blood pressure readings, heart rate, and even genetic test results.
Modern digital devices measure several health parameters. Fitbit trackers use sensors such as accelerometers to tell how many steps we’ve taken in a day or how fast we’ve been walking. When can such novel health measures function as medical biomarkers?
https://www.youtube.com/watch?v=Y74GllySfk8
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You are on the PRO Robots channel and today we are going to talk about the main trends in science and technology for the next 10 years. How will the world of robotics change in 2022 and what will happen in the next 10 years? Experts say robots will become as commonplace in our lives as smartphones and laptops. Watch the top robotics trends in one video!
