An efficient new chip could be used for implantable medical sensors
Source: “The Phoenix Processor: a 30pW Platform for Sensor Applications”
Mingoo Seok et al.
IEEE Symposium on VLSI Circuits, June 2008
Results: Researchers at the University of Michigan have designed a chip less than one millimeter square that uses about a 10th as much energy as the most energy-efficient chips on the market.
Why it matters: The chip could be a boon to sensor design. Its small size–along with the energy savings it provides, which reduce the size of the battery needed–makes it feasible to build sensors that could be implanted under the skin to gauge glucose levels in subcutaneous fluid, or in contact lenses to monitor pressure on the eye.
Methods: Since sensor chips are inactive most of the time, the researchers focused on reducing the amount of energy wasted when the chip is in sleep mode. They redesigned the chip to use less memory (a big source of energy leakage), in part by incorporating hardware for data compression. Next, they reduced the small amounts of power that most transistors leak even when turned off, opting for slightly larger transistors that leak less. They also added special transistors that completely shut off the power supply to the processing transistors when they’re not in use.
Next Steps: The researchers will add a battery to the chip and develop a way to wirelessly download data from it.
A two-layer system stops intelligent denial-of-service attacks
Source: “Mitigating Application-Level Denial of Service Attacks on Web Servers: A Client-Transparent Approach”
Mudhakar Srivatsa et al.
ACM Transactions on the Web, July 2008: 15
Results: Researchers at IBM’s T. J. Watson Research Center and Georgia Tech have developed new security software that minimizes the effects of a type of attack that ties up websites with automated requests, preventing people from using them. The software is tailored to websites that host applications, such as word-processing and interactive-shopping programs.
Why it matters: Denial-of-service attacks can shut down websites, potentially costing millions in revenue. They’re particularly difficult to prevent on websites that host applications, since the automated requests can look very similar to requests from real website users. Distinguishing legitimate users from attackers usually requires cumbersome and inconvenient procedures for logging in to a site. The new software avoids this requirement.
Methods: The researchers wrote algorithms for two filtering systems that prevent attacks. The first limits the total number of requests to the website; the second gives priority to certain users on the basis of what they do on the site. For example, a user who frequently hits the “buy” button will be given higher priority, while users making a quick succession of demanding requests–for example, to download many large image files–will be given a low priority. Would-be attackers would tend to make more requests that use up a lot of bandwidth, memory, or processing power but would not perform valuable actions such as making purchases, so they would be flagged; their access to the site would be reduced and eventually cut off.
Next steps: To use the system, programmers must categorize the activities of a website’s users and assign values to each activity. The researchers’ system currently provides an interface that allows programmers to do this. They plan to improve the interface, developing tools to help programmers make the necessary judgments.