GECCO 2006
AIS Session
Title: Properties of the Bersini Experiment on Self-Assertion
Author: Werner Dilger, Steve Strangfeld
Abstract: The approach of H. Bersini to shape-spaces and in particular his
definition of affinity are analysed. It is shown that the definition of
the affinity function in Bersini style implies a special form of an
affinity region, namely a rhombus. However, variants of the function
can be defined with rectangular or square but rotated affinity
regions. In all cases, the affinity function has the form of a pyramid
over the affinity region. The definition of the affinity function can be
modified in such a way that it describes a lopsided pyramid.
Experimental results with a reimplementation of Bersini's
simulation procedure show that the form of the affinity region has a
strong influence on the form of the recognition/tolerance separation
of the shape-space.
Title: Applicability Issues of the Real-Valued Negative Selection Algorithms
Author: Zhou Ji, Dipankar Dasgupta
Abstract: The paper examines various applicability issues of the negative
selection algorithms (NSA). Recently, concerns were
raised on the use of NSAs, especially those using real-valued
representation. In this paper, we argued that many reported
issues are either due to improper usage of the method or general
difficulties which are not specific to negative selection
algorithms. On the contrary, the experiments with synthetic
data and well-known real-world data show that NSAs have
great flexibility to balance between efficiency and robustness,
and to accommodate domain-oriented elements in the
method, e.g. various distance measures. It is to be noted
that all methods are not suitable for all datasets and data
representation plays a major role.
Title: A Retrovirus Inspired Algorithm for Virus Detection & Optimization
Author: Kenneth S Edge, Gary B Lamont, Richard A Raines
Abstract: In the search for a robust and efficient algorithm to be used for
computer virus detection, we have developed an artificial immune
system genetic algorithm (REALGO) based on the human
immune system's use of reverse transcription ribonucleic acid
(RNA). The REALGO algorithm provides memory such that
during a complex search the algorithm can revert back to and
attempt to mutate in a different "direction" in order to escape
local minima. In lieu of non-existing virus generic templates,
validation is addressed by using an appropriate variety of function
optimizations with landscapes believed to be similar to that ofvirus
detection. It is empirically shown that the REALGO
algorithm finds "better" solutions than other evolutionary
strategies in four out of eight test functions and finds equally
"good" solutions in the remaining four optimization problems.
Title: Immune Anomaly Detection Enhanced with Evolutionary Paradigms
Author: Marek Ostaszewski, Franciszek Seredynski, Pascal Bouvry
Abstract: The paper presents an approach based on principles of immune systems to the anomaly detection problem. Flexibility and efficiency of the anomaly detection system are achieved by building a model of network behavior based on the selfnonself space paradigm. Covering both self and nonself spaces by hyperrectangular structures is proposed. Structures corresponding to self-space are built using a training set from this space. Hyperrectangular detectors covering nonself space are created using niching genetic algorithm. A coevolutionary algorithm is proposed to enhance this process. Results of experiments show a high quality of intrusion detection, which outperform the quality of recently proposed approach based on hypersphere representation of self-space.
Poster Session
Title: An Artificial Immune System and its Integration into an Organic Middleware for Self-Protection
Author: Andreas Pietzowski, Benjamin Satzger, Wolfgang Trumler, Theo Ungerer
Abstract: Our human body is well protected by antibodies from our
biological immune system. This protection system matured
over millions of years and has proven its functionality. In
our research we are transfering techniques of a biological immune
system to a computer based environment in order to
design a self-protecting middleware which isn't vulnerable
to malicious events. First off this paper proposes an artificial
immune system (AIS) and evaluates optimal parameter
settings. As the first research we show up the correlation
between the size of a system and the length of the receptors
used within antibodies for an efficient detection. Further on
we describe the integration of the immune system into our
organic middleware AMUN and afterwards we propose optimization
techniques to minimize the memory space needed
for storing the antibodies and to speedup the time needed
for detecting malicious objects.
Title: A Dynamic Approach to Artificial Immune Systems utilizing Neural Networks
Author: Stefan Schadwinkel, Werner Dilger
Abstract: The purpose of this work is to propose an immune-inspired
setup to use a self-organizing map as a computational model
for the interaction of antigens and antibodies. The proposed
approach may be used as a part in other immune algorithms,
or can possibly be used to detect anomalies in time series
data.
Other Sessions
Title: A Comparative Study of Immune System Based Genetic Algorithms in Dynamic Environments
Author: Shengxiang Yang
Abstract: Diversity and memory are two major mechanisms used in
biology to keep the adaptability of organisms in the everchanging
environment in nature. These mechanisms can be
integrated into genetic algorithms to enhance their performance
for problem optimization in dynamic environments.
This paper investigates several GAs inspired by the ideas of
biological immune system and transformation schemes for
dynamic optimization problems. An aligned transformation
operator is proposed and combined to the immune system
based genetic algorithm to deal with dynamic environments.
Using a series of systematically constructed dynamic test
problems, experiments are carried out to compare several
immune system based genetic algorithms, including the proposed
one, and two standard genetic algorithms enhanced
with memory and random immigrants respectively. The experimental
results validate the efficiency of the proposed
aligned transformation and corresponding immune system
based genetic algorithm in dynamic environments.