From the Labs: Information Technology
New publications, experiments and breakthroughs in information technology–and what they mean.
A new device uses heat to fit extra bits on a hard disk
Source: “Heat-assisted magnetic recording by a near-field transducer with efficient optical energy transfer”
William Challener et al.
Nature Photonics 3: 220-224
Results: Researchers at Seagate have developed a way to deliver targeted pulses of heat to the magnetic areas of hard-disk drives. The technology should make it possible to write up to 20 times more data to disks than is possible today.
Why it matters: Hard drives record data when a magnetic head moves across a disk coated with small grains that represent 1s or 0s, depending on their magnetic orientation. To cram more data onto these drives, researchers have been making the grains smaller and smaller. But grains made of conventional materials will become unstable if they’re too small, losing data when they experience small fluctuations in temperature. The new recording method allows the researchers to use materials that are more stable, packing more bits into a given area to increase data storage capacity. In addition to holding more data, the resulting hard drives could be more reliable.
Methods: Today’s magnetic heads can’t write data to the more stable recording media. Heating the grains solves this problem, but it’s been difficult to heat an area small enough to keep surrounding grains from being affected; no conventional lens can focus laser light onto such a tiny spot. The researchers accomplished this by focusing the light with a device called an optical antenna instead of a lens.
Next steps: The company hopes to reduce the concentrated spot of heat from 70 nanometers to 20 nanometers. The engineers are also developing a way to deliver laser light efficiently to the recording head.
Researchers raise privacy concerns about social-network data
Source: “De-Anonymizing Social Networks”
Arvind Narayanan and Vitaly Shmatikov
IEEE Symposium on Security and Privacy, May 17-20, 2009, Oakland, CA
Results: Researchers from the University of Texas at Austin designed an algorithm that can identify individuals using supposedly anonymous information that social-networking websites could provide to advertisers. In tests using Flickr and Twitter, they were able to assign names to a third of the users who maintained accounts on both sites, with only a 12 percent error rate.
Why it matters: Most social networks plan to make money by sharing data with advertisers. Although personally identifying information such as names and addresses is removed, the new study shows that individuals can still be identified.
Methods: The researchers developed an algorithm that compares publicly available information from one social-networking site–such as a person’s name and list of contacts–with the data that another site might supply to advertisers. The publicly available data is used to help create a map of connections between people. The advertisers’ data is used to create a similar map, with the names, addresses, and other personal information missing. The algorithm can identify features common to both that reveal a person’s identity, even when the maps overlap by as little as 14 percent. The researchers designed the algorithm to start with social-network users who can easily be identified–as few as 30 individuals in 100,000–and then use personal information about those users to fill in details about others.
Next steps: Having demonstrated that the relationship information that makes social-network data useful could also compromise user privacy, the researchers say the solution is to change the privacy laws and corporate practices that govern the sharing of “anonymous” information from such sites.