“The spyware that penetrated his laptop appears to be a Western-made surveillance tool sold to police and intelligence agencies that’s so powerful it can turn on webcams and microphones and grab documents off hard drives…”
“Six days later, another assailant cornered Mansoor on campus and without saying a word dragged him to the ground and punched him in his head until a crowd gathered, he says. Doctors X-rayed his skull, dressed his wounds and gave him a tetanus injection, according to hospital records that describe him as the victim of an assault. “
Big Dog learns to sit, roll over and heel. Our tax dollars at work designing the unstoppable beast that will track us through the forest in our final days.
The first weapon made entirely out of code
An infographic dissecting the nature and ramifications of Stuxnet, the first weapon made entirely out of code. This was produced for Australian TV program HungryBeast on Australia’s ABC1.
It was a winner at this year’s Information Is Beautiful Awards.
Malware designed to build 3-D models of users’ apartments for burglars and assassins
“Newly released malware PlaceRaider sounds like science fiction: It’s Android malware designed to build 3-D models of users’ apartments for burglars and assassins. But PlaceRaider—developed by a team at Indiana University—is very real. The new malware was built as an academic exercise, and it exposes security flaws that government agencies would love to use. More importantly, it also exposes unintended mobile functionality that large companies like Google could easily monetize.”
From Fast Company.
“Researchers have identified five of the genes that shape a person’s face, work that could help scientists better understand facial abnormalities like cleft palate and someday might even help forensic investigators determine what a criminal suspect looks like from crime-scene DNA.”
Read more: http://www.foxnews.com/science/2012/09/16/5-face-shaping-genes-identified
The study was published on September 13th in PLoS Genetics.
“Using DNA samples to recognize a suspect is currently a far-fetched, ‘CSI’-like scenario….
It’s a little less far-fetched in the case of eye and hair color. Kayser and colleagues in August released HIrisPlex, a system that allows researchers to predict eye and hair color from DNA samples, although only from people of European descent. The forensic test is nearly 70 percent accurate in identifying blonds and up to 87.5 percent accurate for dark-haired individuals.”
Autonomous Multi-Floor Indoor Navigation with a Computationally Constrained MAV
This video is simply amazing. This flying robot maps a building internally, going up stairs and returning to its starting point. It is autonomous. What a powerful reconnaissance device.
“This video shows our results on autonomous multi-floor indoor navigation with a quadrotor. We designed a system that is capable of autonomous navigation with real-time performance on a mobile processor using only onboard sensors. Specifically, we address multi-floor mapping with loop closure, localization, planning, and autonomous control, including adaptation to aerodynamic effects during traversal through spaces with low vertical clearance or strong external disturbances. All of the computation is done onboard the 1.6Ghz Intel Atom processor and uses ROS for interprocess communication. Human interaction is limited to provide high-level goals to the robot.”
Real Swarm of Flying Nano Quadrotors Doing Flight Tricks HD
The nerd in me loves these little machines and is impressed with the sophistication of the algos.
The futurist in me would not like to be tracked through a building by a coordinated swarm of flying nano-bots.
These seem best suited for indoor use where there is no danger of gusts of winds, thereby suggesting some simple counter-measures (like a fan).
These bots are well suited for mapping internal spaces as well (video to follow in next post).
We’d like to avoid a war with superhuman machines, because humans would lose — and we’d lose more quickly than is depicted in, say, The Terminator.Luke Muehlhauser, CEO of the Singularity Institute (via reddit)
How the NSA uses GPS Spoofing: from a Washington Post article on ‘Top Secret America’:
“Most people don’t realize when they’re nearing the epicenter of Fort Meade’s, even when the GPS on their car dashboard suddenly begins giving incorrect directions, trapping the driver in a series of U-turns, because the government is jamming all nearby signals.”
“It’s an experiential trap street—an infinite loop—a deliberate cartographic error introduced into the mapping of the world so as to sow detour and digression. A kind of digital baffling, or recursive geography as state defensive tactic.
I’m also curious when we might see this privatized and domesticated—gated communities, for instance, blocking the GPS navigation of their streets in the misguided belief that this will help protect them from future burglary, effectively delisting themselves from public cartographic records. Perhaps the future of neighborhood security lies in the privatized repurposing of advanced signal-jamming technology, the misleading lamination of other, false maps onto the streets as they really exist.”
As Brain-Computer Interfaces Approach the Mainstream, Hackers Demonstrate Security Vulnerabilities, “Backdoor for the Brain”
To extract this information, the researchers rely on what’s known as the P300 response — a very specific brainwave pattern …that occurs when you recognize something that is meaningful (a person’s face), or when you recognize something that fits your current task (a hammer in the shed).
The researchers basically designed a program that flashes up pictures of maps, banks, and card PINs, and makes a note every time your brain experiences a P300.
Afterwards, it’s easy to pore through the data and work out — with fairly good accuracy — where a person banks, where they live, and so on.
In a real-world scenario, the researchers foresee a game that is specially tailored by hackers to extract sensitive information from your brain — or perhaps an attack vector that also uses social engineering to lull you into a false sense of security. It’s harder to extract data from someone who knows they’re being attacked — as interrogators and torturers well know.
Abstract: “We investigate a family of poisoning attacks against Support Vector Machines (SVM). Such attacks inject specially crafted training data that increases the SVM’s test error. Central to the motivation for these attacks is the fact that most learning algorithms assume that their training data comes from a natural or well-behaved distribution. However, this assumption does not generally hold in security-sensitive settings. As we demonstrate, an intelligent adversary can, to some extent, predict the change of the SVM’s decision function due to malicious input and use this ability to construct malicious data.”