Black Box Records in Automobiles
Proposed new rules in the U.S.
Entries Tagged "privacy"
Page 86 of 145
Mobile Phone Privacy App Contest
Entries due by the end of the month.
Fingerprint Scanner that Works at a Distance
Scanning fingerprints from six feet away.
Slightly smaller than a square tissue box, AIRprint houses two 1.3 megapixel cameras and a source of polarized light. One camera receives horizontally polarized light, while the other receives vertically polarized light. When light hits a finger, the ridges of the fingerprint reflect one polarization of light, while the valleys reflect another. “That’s where the real kicker is, because if you look at an image without any polarization, you can kind of see fingerprints, but not really well,” says Burcham. By separating the vertical and the horizontal polarization, the device can overlap those images to produce an accurate fingerprint, which is fed to a computer for verification.
No information on how accurate it is, but it’ll only get better.
The Inner Workings of an FBI Surveillance Device
This FBI surveillance device, designed to be attached to a car, has been taken apart and analyzed.
A recent ruling by the 9th U.S. Circuit Court of Appeals affirms that it’s legal for law enforcement to secretly place a tracking device on your car without a warrant, even if it’s parked in a private driveway.
FBI Surveillance Tools
Interesting blog post from EFF.
The Era of "Steal Everything"
Good comment:
“We’re moving into an era of ‘steal everything’,” said David Emm, a senior security researcher for Kaspersky Labs.
He believes that cyber criminals are now no longer just targeting banks or retailers in the search for financial details, but instead going after social and other networks which encourage the sharing of vast amounts of personal information.
As both data storage and data processing becomes cheaper, more and more data is collected and stored. An unanticipated effect of this is that more and more data can be stolen and used. As the article says, data minimization is the most effective security tool against this sort of thing. But—of course—it’s not in the database owner’s interest to limit the data it collects; it’s in the interests of those whom the data is about.
Stolen Camera Finder
Here’s a clever Web app that locates your stolen camera by searching the EXIF data on public photo databases for your camera’s serial number.
Software as Evidence
Increasingly, chains of evidence include software steps. It’s not just the RIAA suing people—and getting it wrong—based on automatic systems to detect and identify file sharers. It’s forensic programs used to collect and analyze data from computers and smart phones. It’s audit logs saved and stored by ISPs and websites. It’s location data from cell phones. It’s e-mails and IMs and comments posted to social networking sites. It’s tallies from digital voting machines. It’s images and meta-data from surveillance cameras. The list goes on and on. We in the security field know the risks associated with trusting digital data, but this evidence is routinely assumed by courts to be accurate.
Sergey Bratus is starting to look at this problem. His paper, written with Ashlyn Lembree and Anna Shubina, is “Software on the Witness Stand: What Should it Take for Us to Trust it?”
We discuss the growing trend of electronic evidence, created automatically by autonomously running software, being used in both civil and criminal court cases. We discuss trustworthiness requirements that we believe should be applied to such software and platforms it runs on. We show that courts tend to regard computer-generated materials as inherently trustworthy evidence, ignoring many software and platform trustworthiness problems well known to computer security researchers. We outline the technical challenges in making evidence-generating software trustworthy and the role Trusted Computing can play in addressing them.
From a presentation he gave on the subject:
Constitutionally, criminal defendants have the right to confront accusers. If software is the accusing agent, what should the defendant be entitled to under the Confrontation Clause?
[…]
Witnesses are sworn in and cross-examined to expose biases & conflicts—what about software as a witness?
New French Law Reduces Website Security
I didn’t know about this:
The law obliges a range of e-commerce sites, video and music services and webmail providers to keep a host of data on customers.
This includes users’ full names, postal addresses, telephone numbers and passwords. The data must be handed over to the authorities if demanded.
Police, the fraud office, customs, tax and social security bodies will all have the right of access.
The social benefits of anonymity aside, we’re all more secure if these websites do not have a file of everyone’s plaintext password.
EDITED TO ADD (4/12): Seems that the BBC article misstated the law. Companies have to retain information they already collect for a year after it is no longer required. So if they’re not already storing plaintext passwords, they don’t have to start.
Pinpointing a Computer to Within 690 Meters
This is impressive, and scary:
Every computer connected to the web has an internet protocol (IP) address, but there is no simple way to map this to a physical location. The current best system can be out by as much as 35 kilometres.
Now, Yong Wang, a computer scientist at the University of Electronic Science and Technology of China in Chengdu, and colleagues at Northwestern University in Evanston, Illinois, have used businesses and universities as landmarks to achieve much higher accuracy.
These organisations often host their websites on servers kept on their premises, meaning the servers’ IP addresses are tied to their physical location. Wang’s team used Google Maps to find both the web and physical addresses of such organisations, providing them with around 76,000 landmarks. By comparison, most other geolocation methods only use a few hundred landmarks specifically set up for the purpose.
The new method zooms in through three stages to locate a target computer. The first stage measures the time it takes to send a data packet to the target and converts it into a distance—a common geolocation technique that narrows the target’s possible location to a radius of around 200 kilometres.
Wang and colleagues then send data packets to the known Google Maps landmark servers in this large area to find which routers they pass through. When a landmark machine and the target computer have shared a router, the researchers can compare how long a packet takes to reach each machine from the router; converted into an estimate of distance, this time difference narrows the search down further. “We shrink the size of the area where the target potentially is,” explains Wang.
Finally, they repeat the landmark search at this more fine-grained level: comparing delay times once more, they establish which landmark server is closest to the target. The result can never be entirely accurate, but it’s much better than trying to determine a location by converting the initial delay into a distance or the next best IP-based method. On average their method gets to within 690 metres of the target and can be as close as 100 metres—good enough to identify the target computer’s location to within a few streets.
Sidebar photo of Bruce Schneier by Joe MacInnis.