Ants Vs. Worms: New Computer Security Mimics Nature.

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ScienceDaily (Sep. 28, 2009) — In the never-ending battle to protect computer networks from intruders, security experts are deploying a new defense modeled after one of nature’s hardiest creatures — the ant.

Unlike traditional security devices, which are static, these “digital ants” wander through computer networks looking for threats, such as “computer worms” — self-replicating programs designed to steal information or facilitate unauthorized use of machines. When a digital ant detects a threat, it doesn’t take long for an army of ants to converge at that location, drawing the attention of human operators who step in to investigate.
The concept, called “swarm intelligence,” promises to transform cyber security because it adapts readily to changing threats.
“In nature, we know that ants defend against threats very successfully,” explains Professor of Computer Science Errin Fulp, an expert in security and computer networks. “They can ramp up their defense rapidly, and then resume routine behavior quickly after an intruder has been stopped. We were trying to achieve that same framework in a computer system.”
Current security devices are designed to defend against all known threats at all times, but the bad guys who write malware — software created for malicious purposes — keep introducing slight variations to evade computer defenses.
As new variations are discovered and updates issued, security programs gobble more resources, antivirus scans take longer and machines run slower — a familiar problem for most computer users.
Glenn Fink, a research scientist at Pacific Northwest National Laboratory (PNNL) in Richland, Wash., came up with the idea of copying ant behavior. PNNL, one of 10 Department of Energy laboratories, conducts cutting-edge research in cyber security.
Fink was familiar with Fulp’s expertise developing faster scans using parallel processing — dividing computer data into batches like lines of shoppers going through grocery store checkouts, where each lane is focused on certain threats. He invited Fulp and Wake Forest graduate students Wes Featherstun and Brian Williams to join a project there this summer that tested digital ants on a network of 64 computers.
Swarm intelligence, the approach developed by PNNL and Wake Forest, divides up the process of searching for specific threats.
“Our idea is to deploy 3,000 different types of digital ants, each looking for evidence of a threat,” Fulp says. “As they move about the network, they leave digital trails modeled after the scent trails ants in nature use to guide other ants. Each time a digital ant identifies some evidence, it is programmed to leave behind a stronger scent. Stronger scent trails attract more ants, producing the swarm that marks a potential computer infection.”
In the study this summer, Fulp introduced a worm into the network, and the digital ants successfully found it. PNNL has extended the project this semester, and Featherstun and Williams plan to incorporate the research into their master’s theses.
Fulp says the new security approach is best suited for large networks that share many identical machines, such as those found in governments, large corporations and universities.
Computer users need not worry that a swarm of digital ants will decide to take up residence in their machine by mistake. Digital ants cannot survive without software “sentinels” located at each machine, which in turn report to network “sergeants” monitored by humans, who supervise the colony and maintain ultimate control.
Adapted from materials provided by Wake Forest University. Original article written by Eric Frazier, Office of Communications and External Relations.

Reconstruct Mars Automatically In Minutes.

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ScienceDaily (Sep. 18, 2009) — A computer system is under development that can automatically combine images of the Martian surface, captured by landers or rovers, in order to reproduce a three dimensional view of the red planet. The resulting model can be viewed from any angle, giving astronomers a realistic and immersive impression of the landscape.

The new development has been presented at the European Planetary Science Congress in Potsdam by Dr Michal Havlena.
“The feeling of ‘being right there’ will give scientists a much better understanding of the images. The only input we need are the captured raw images and the internal camera calibration. After minutes of computation on a standard PC, a three dimensional model of the captured scene is obtained,” said Dr Havlena.
The growing amount of available imagery from Mars is nearly impossible to handle for the manual image processing techniques used to date. The new automated method, which allows fast high quality image processing, was developed at the Center for Machine Perception of the Technical University of Prague, under the supervision of Tomas Pajdla, as a part of the EU FP7 Project PRoVisG.
From the technical point of view, the image processing consists of three stages: the first step is determining the image order. If the input images are unordered, i.e. they do not form a sequence but still are somehow connected, a state-of-the-art image indexing technique is able to find images of cameras observing the same part of the scene. To start with, up to a thousand features on each image are detected and “translated” into visual words, according to a visual vocabulary trained on images from Mars. Then, starting from an arbitrary image, the following image is selected if it shares the highest number of visual words with the previous image.
The second step of the pipeline, the so-called ‘structure-from-motion computation’, helps scientists determine the accurate camera positions and rotations in three dimensional space. Just five corresponding features are enough to obtain a relative camera pose between the two images that have been selected as sequential.
The last and most important step is the so-called ‘dense 3D model generation’ of the captured scene, which essentially creates and fuses the Martian surface depth maps. To do this, the model uses the disparities (parallaxes) present in images taken at two distinct camera positions, which were identified in the second step.
“The pipeline has already been used successfully to reconstruct a three dimensional model from nine images captured by the Phoenix Mars Lander, which were obtained just after performing some digging operation on the Mars surface,” said Dr Havlena.
“The challenge is now to reconstruct larger parts of the surface of the red planet, captured by the Mars Exploration Rovers Spirit and Opportunity,” concluded Dr Havlena.
Adapted from materials provided by Europlanet Media Centre, via AlphaGalileo.