Networks

(a subtopic of Applications)

"Researchers in business and government labs are building systems that will challenge what it means to be an IT worker by automating many of the monitoring and maintenance tasks done today by hand. ... The motivating factor behind it all: to wage war on complexity. The interlocking pieces of software that make up business computer networks will soon be beyond the comprehension of most IT workers. Plus, these complex systems tend to be fragile, breaking down when even minor changes are made" - Computer, Heal Thyself

Striving for dependability. By Armando Fox and David Patterson. Sidebar to their primary article: Self-Repairing Computers. Scientific American (June 2003). "As the costs of administration, oversight and downtime expand in response, scientists and engineers in the computer industry are working to enhance the dependability of their products. Significantly, many of their efforts aim to take humans (and the errors they inevitably engender) out of the loop. ... IBM's scheme borrows ideas from control theory (the use of feedback to stabilize closed-loop systems) and artificial intelligence (mimicking or otherwise capturing expert human skills or intelligence to solve complex problems). These concepts will help create data centers that can diagnose problems on their own, adjust their configurations to match changes in demand, repair themselves and defend against hacker attacks. Drawing an analogy with the body's autonomic nervous system, IBM's management calls this goal Autonomic Computing."

UU Seeking to develop networks that think for themselves. University of Ulster Online (January 9, 2006). "The University of Ulster has won a competitive bid to take part in a EU-funded ‘blue skies’ research project to develop the next generation of networks - networks that can think for themselves. The three year project has a 5m Euro (£3.36m) budget and involves 14 partners from throughout Europe. The University’s team -- Maurice Mulvenna and Dr Chris Nugent, senior lecturers in Computer Science in the School of Computing and Mathematics and Dr Kevin Curran, lecturer in Computer Science in the School of Computing and Intelligent Systems -- will contribute their expertise in next-generation networking and artificial intelligence systems. Mr Mulvenna said: ... 'Essentially the aim of CASCADAS is to develop networks that can -- to an extent -- think for themselves. Ideally the systems could run themselves better with little human influence. Of course, this is of great interest to business as it offers lower cost services in computing and networks.'"

Promise of intelligent networks. By Mark Ward. BBC (February 24, 2003). "US researchers are working on ways to make wireless computer networks organise them. Computer scientists at Intel are developing mesh networking technologies that can automatically work out the best route for data as demand changes or devices join and leave the system. The researchers believe such automatic networking systems will be needed as the numbers of devices that can communicate wirelessly proliferate. ... Mr [Mike] Witteman and his colleagues are working on ways to instil wireless devices with the intelligence to work out all the different routes that data can take from one point to another in any network they form."

Cornell's Jon Kleinberg. TRN's View from the High Ground (December 5, 2005). "Technology Research News Editor Eric Smalley carried out an email conversation with Jon Kleinberg, a Professor of Computer Science at Cornell University and a member of the Visiting Faculty Program at the IBM Almaden Research Center.Kleinberg's research is about the interface of networks and information, and spans computer network analysis and routing, data mining, comparative genomics, and protein structure. His work on network analysis helped form the foundation for the current generation of Internet search engines, and his work on 'small world' networks has advanced sociology as well as computer network design. ... TRN: Tell me about the trends in network theory and analysis.Kleinberg: Network theory is a subject that blends ideas from many areas. It's grown rapidly as a field over the past decade, driven by the realization that many phenomena in technology, in the physical and natural sciences, and in the social sciences can be expressed in the common framework of networks.Computer scientists have used network analysis to help people search and navigate the Web; social scientists have had to deal with large-scale data on the networks of interactions that exist within companies, financial markets, and professional communities; and biologists have found that the networks of interactions within a cell's metabolism provide insight into basic biological processes.The fundamental theme here is to approach networks phenomenologically -- rather than treating networks as things to be designed and built, we view them as organic entities that arise naturally in the physical world, in the virtual world, and in society. ..."

MIND (Machine Learning for Intrusion Detection) project at Fraunhofer FIRST Institute for Computer Architecture and Software Technology. "Machine learning technologies, including various methods from statistics, Artificial Intelligence and data mining, are excellent tools for improving IDS [intrusion detection systems] quality and developing new approaches to intrusion detection. The MIND project, which is funded by the German Federal Ministry for Education and Research (BMBF), is applying and further developing modern machine learning technologies for intrusion detection."

IBM Unveils New Solution to Eliminate Insider Attacks - Employees Emerging as the Biggest Security Threat for Business. IBM Press Room (February 24, 2006). "IBM today announced a new fraud detection capability that monitors users' online transactions for questionable activity. The new solution goes beyond today's traditional identity verification procedures by analyzing users' online behavior to help determine whether the actual use of the data is valid. This analysis can be done historically, tracking users' past activity, or prospectively by comparing realtime behavior to normal patterns of activity."

Computational Vulnerability Analysis for Information Survivability. By Howard Shrobe. AI Magazine 23(4): Winter, 2002, 81-94. "The infrastructure of modern society is controlled by software systems. These systems are vulnerable to attacks; several such attacks, launched by 'recreation hackers,' have already led to severe disruption. However, a concerted and planned attack whose goal is to reap harm could lead to catastrophic results (for example, by disabling the computers that control the electrical power grid for a sustained period of time). The survivability of such information systems in the face of attacks is therefore an area of extreme importance to society. This article is set in the context of self-adaptive survivable systems: software that judges the trustworthiness of the computational resources in its environment and that chooses how to achieve its goals in light of this trust model. Each self-adaptive survivable system detects and diagnoses compromises of its resources, taking whatever actions are necessary to recover from attack. In addition, a long-term monitoring system collects evidence from intrusion detectors, firewalls, and all the selfadaptive components, building a composite trust model used by each component. Self-adaptive survivable systems contain models of their intended behavior; models of the required computational resources; models of the ways in which these resources can be compromised; and finally, models of the ways in which a system can be attacked and how such attacks can lead to compromises of the computational resources. In this article, I focus on computational vulnerability analysis: a system that, given a description of a computational environment, deduces all the attacks that are possible. In particular, its goal is to develop multistage attack models in which the compromise of one resource is used to facilitate the compromise of other, more valuable resources. Although the ultimate aim is to use these models online as part of a self-adaptive system, there are other offline uses as well that we are deploying first to help system administrators assess the vulnerabilities of their computing environment."

Computers that run themselves. The Economist Technology Quarterly (September 19, 2002). "Computing: For decades, scientists have concentrated on making computers more powerful. Now they want to build systems that are smart enough to look after themselves."

On the Backs of Ants - New networks mimic the behavior of insects and bacteria. By Kimberly Patch. Technology Review (March 19, 2003). "Drawing heavily on the chemistry of biology, researchers from Humboldt University in Germany have devised a way for electronic agents to efficiently assemble a network without relying on a central plan. The researchers modeled their idea on the methods of insects and other life forms whose communications lack central planning, but who manage to form networks when individuals secrete and respond to chemical trails. ... Rather than determine the structure of a network in a top-down approach of hierarchical planning, agents found nodes and created connections in a bottom-up process of self-organization."

• Also see: Multi-Agent Systems

A War of Robots, All Chattering on the Western Front. By Noah Shactman. The New York Times [July 11, 2002 (no-fee reg. req'd)]. "An association of nearly 300 scientists and engineers spread across 45 project teams and coordinated by the Office of Naval Research is about a year and a half into a five-year, $11 million effort to determine what it will take to build such a system. The project is called Multimedia Intelligent Network of Unattended Mobile Agents, or Minuteman (not to be confused with the nuclear missiles). ... This flexible 'network of networks' structure not only allows communications to stay up when individual drones go down but also enables the network to reconfigure itself to maximize bandwidth and to meet goals on the battlefield. Robot planes would constantly shift position to communicate with one another. This continuous reconfiguration is part of an attempt by Allen Moshfegh, director of the Minuteman project, to mimic one of the most elegant of systems for transferring information: the human brain. In the brain, groups of neurons quickly form around a particular goal like reaching for a newspaper, then recombine for the next task, like turning the page."

"SRI International's System Design Laboratory has been actively involved in intrusion-detection research since 1983. Our first project, the Intrusion Detection Expert System (IDES), was a rule-based expert system trained to detect known malicious activity. That system was polished and enhanced to form NIDES, the Next-Generation Intrusion Detection Expert System. Currently, our research focuses on EMERALD: Event Monitoring Enabling Responses to Anomalous Live Disturbances, a modern system designed to detect and respond to today's network attacks."

• Also see: Cyber Attack Plan Recognition Engine (CAPRE), a collaboration between the Artificial Intelligence Center and Magnus Almgren in SRI's System Design Laboratory.
• "My own research in intrusion detection concerned using feature selection to build better classifiers explicitly for use as intrusion detection systems. Results of this work were presented at the 17th National Computer Security Conference in 1994 in the paper titled 'Artificial Intelligence and Intrusion Detection: Current and Future Directions.'"
  • You can access this paper from his site.

Intelligent Agents for Intrusion Detection. Helmer, G., Wong, J., Honavar, V. and Miller, L. (1998). (From the list of publications of the Artificial Intelligence Research Laboratory, Department of Computer Science, Iowa State University.) An Introduction to Intrusion Detection. By Aurobindo Sundaram. ACM Crossroads Student Magazine 2.4 (April 1996). "This paper discusses why intrusion detection systems are needed, the main techniques, present research in the field, and possible future directions of research." Cyber Information Assurance and Decision Support Division (CIADS), Information Systems Laboratory, The University of Texas at Austin.

Security and Assurance in Information Security Laboratory (SAIT) at Florida State University. Computer, Heal Thyself. By Karyl Scott. Information Week (April 1, 2002). "Too bad computers aren't more like people. When we work harder, our hearts beat faster. When we're hot, we sweat. But in the 54 years since British mathematician Alan Turing introduced the notion of artificial intelligence, computer scientists haven't delivered anything close to a self-aware and self-healing computer. That may change soon enough. Researchers in business and government labs are building systems that will challenge what it means to be an IT worker by automating many of the monitoring and maintenance tasks done today by hand. ... The motivating factor behind it all: to wage war on complexity. The interlocking pieces of software that make up business computer networks will soon be beyond the comprehension of most IT workers. Plus, these complex systems tend to be fragile, breaking down when even minor changes are made. ... The ultimate goal of adaptive computing isn't just to have smart, self-healing systems, but to have smart business processes. That's the prize researchers at Sun are aiming for with a product-forecasting system that constantly monitors its own performance and tests assumptions about business execution."

• Also see: In HAL's Footsteps - Real progress is being made in developing IT systems that do a better job of monitoring, analyzing, and fixing problems without human intervention. By Darrell Dunn. InformationWeek (October 10, 2005).

The Once and Future IT - Autonomic computing may already be here, but the real payoff is three to 10 years away. By Matt Hamblen. Computerworld (September 8, 2003). "The central promise of autonomics is that IT workers won't need to do as many routine chores such as restore failed servers or provision switches and routers. Autonomics can free up IT workers for higher-level tasks and give them more time to spend with business managers to find ways to make systems work for the needs of their companies. But is there anything new about autonomics? Is it simply old technology incrementally improved and repackaged with a new buzzword? Perhaps. But IT managers keenly understand the new benefits of autonomics, while acknowledging that the concept has a long history. 'Autonomics is definitely evolutionary, and we don't look at it as a distinct point' when a company suddenly has it, says Ed Toben, CIO at Colgate-Palmolive Co. in New York. His company has widely deployed IBM systems management products, including Tivoli software, to keep its SAP system running on servers and storage gear in 55 countries. 'For us, autonomics means that systems can be self-managed, and the more you can do that, the better,' says Toben. ... Gartner [Inc.] lists 22 technologies related to autonomics that are coming in the next decade."

Two articles from the June 2002 issue of New Architect:

• Server, Heal Thyself - The Quest for Autonomic Computing. By Jay Lyman.
• Deus Ex Machina. [You'll have to scroll down the page to find the article.] By Al Williams. "How will machines replace administrators? With artificial intelligence (AI), we're told. However, AI is a much broader concept than you might expect. Imagine how you'd feel if you asked someone how they implemented an e-commerce site, and they replied, 'Networking, of course!' The reality is that AI is a general term for many specific techniques. In the quest for homeostatic servers, two AI technologies seem to be the most promising: expert systems and neural networks."

IBM's eLiza - Self-healing IT. By Maggie Biggs. ZD Net (March 22, 2002). "The new eLiza technologies let IBM products fix themselves, taking the human element out of the picture. As a result, network administrators can focus their efforts on more critical work. eLiza involves not only all of IBM's products and services, but those of other technology providers such as Nortel Networks and BMC Software. This isn't the first we're seeing of eLiza. A mid-1960s IBM project--known as ELIZA--focused on communication between humans and computers and was the precursor to much of today's artificial intelligence technology. IBM's new eLiza initiative also focuses on supplying intelligence, but for enterprise infrastructures rather than between humans and computers."

• "Although certain aspects of AI will undoubtedly make contributions to autonomic computing, autonomic computing does not have as its primary objective the emulation of human thought." - from the definition of "Artificial Intelligence" in IBM's Autonomic Computing Glossary

Biometrics Research. From the Pattern Recognition and Image Processing Lab, Department of Computer Science And Engineering, Michigan State University. "Biometrics can be used to prevent unauthorized access to ATMs, cellular phones, smart cards, desktop PCs, workstations, and computer networks."

• also see our collection of resources about biometrics

Two papers from the Useful Research Resources page providedthe Department of Systems and Computer Engineering Network Management and Artificial Intelligence Laboratory at Carleton University:

• Experience and Trends in AI for Network Monitoring and Diagnosis, by Christopher Leckie.

Proactive Network Management Using Remote Monitoring and Artificial Intelligence Techniques, by Analucia S.M. de Franceschi, Marco Antonio da Rocha, Henrique L. Weber, and Carlos B. Westphall. In Proceedings of the 2nd IEEE Symposium on Computers and Communications (ISCC 1997).

How Routing Algorithms Work. By Roozbeh Razavi. Howstuffworks.