Information Technology Reference
In-Depth Information
On Permutation Masks in Hamming
Negative Selection
Thomas Stibor
1
, Jonathan Timmis
2
, and Claudia Eckert
1
1
Department of Computer Science
Darmstadt University of Technology
{stibor, eckert}@sec.informatik.tu-darmstadt.de
2
Departments of Electronics and Computer Science
University of York, Heslington, York
jtimmis@cs.york.ac.uk
Abstract.
Permutation masks were proposed for reducing the number
of holes in Hamming negative selection when applying the
r
-contiguous
or
r
-chunk matching rule. Here, we show that (randomly determined)
permutation masks re-arrange the semantic representation of the under-
lying data and therefore shatter self-regions. As a consequence, detec-
tors do not cover areas around self regions, instead they cover randomly
distributed elements across the space. In addition, we observe that the
resulting holes occur in regions where actually no self regions should
occur.
1
Introduction
Applying negative selection for anomaly detection problems has been undertaken
extensively [1,2,3,4]. Anomaly detection problems, also termed one-class classifi-
cation, can be considered as a type of pattern classification problem, where one
tries to describe a single class of objects, and distinguish that from all other pos-
sible objects. More formally, one-class classification is a problem of generating
decision boundaries that can successfully distinguish between the normal and
anomalous class. Hamming negative selection is an immune-inspired technique
for one-class classification problems. Recent results, however, have revealed sev-
eral problems concerning algorithm complexity of generating detectors [5,6,7]
and determining the proper matching threshold to allow for the generation of
correct generalization regions [8]. In this paper we investigate an extended tech-
nique for Hamming negative selection: permutation masks. Permutation masks
are immunologically motivated by lymphocyte diversity. Lymphocyte diversity
is an important property of the immune system, as it enables a lymphocyte to
reacting to many substances, i.e. it induces diversity and generalization. This
kind of generalization process inspired Hofmeyr [3,9] to propose a similar coun-
terpart for use in Hamming negative selection. Hofmeyr introduced permutation
masks in order to reduce the number of undetectable elements. It was argued
that permutation masks could be useful for covering the non-self space eciently
when varying the representation by means of permutation masks (see Fig. 1).
