Arms Race Within Information Ecosystems

Document type: Journal Articles
Article type: Original article
Peer reviewed: Yes
Full text:
Author(s): Bengt Carlsson, Rune Gustavsson
Title: Arms Race Within Information Ecosystems
Journal: Lecture Notes in Artificial Intelligence
Year: 2001
Volume: 2182
Pagination: 202-207
ISSN: 0302-9743
Publisher: Springer Verlag
ISI number: 000180978200021
Organization: Blekinge Institute of Technology
Department: Department of Software Engineering and Computer Science (Institutionen för programvaruteknik och datavetenskap)
Dept. of Software Engineering and Computer Science S-372 25 Ronneby
+46 455 38 50 00
Authors e-mail:,
Language: English
Abstract: Interacting agents of exploiters and users within an information ecosystem may be regarded both as biological beings and as part of an economic system of infohabitants. A protection system can be implemented as a filter governing the access to assets. Typically we will have a chain of attacks and countermeasures concerning this access to the desired assets. We model this process as an arms race. We base our model on a process model of a protection system based on exposure time. A user's reaction against an exploiter measure could either be a direct response to the measure or an attempt to anticipate future attacks by more general means of defeating the protection of the exploiter agent. When anticipating future attacks and countermeasures, both users and exploiters will improve their methods and tools due to an arms race. Our arms race model refines the competition as modeled in computational markets to model aspects which typically arise when societies grow beyond what can be controlled in a centralized manner. A dynamic, evolving and robust ecosystem of autonomous agents is sometimes a preferred and possible outcome of the arms race as a hardening process.
Subject: Computer Science\General
Keywords: Information ecosystems, Arms race, protection system
Note: in eds. M., Klusch, and F., Zambonelli, Cooperative Information Agents V, Lecture Notes in Artificial Intelligence 2182, pp. 202-207 Springer Verlag, , 2001