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 Programme
Overview
Detailed
Programme
CHAIR: ANDREW SUNG
Time: Wednesday,
March 23rd, 16h00-17h45
| CS-1 |
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| Title: |
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Solving The Roots of Cyclic-Code
Generated Polynomial by Using Evolutionary Computation |
| Author(s): |
Kangshun Li,
Yuanxiang Li,
Chong Teng,
Yuhua Wang |
| Abstract: |
The data integrity in computer security is a
key component of what we call trustworthy computing, and one
of the most important issues in data integrity is to detect
and correct error codes, which is also a crucial step in software
and hardware design. But the key step to detect and correct
error codes is to solve the legal-code of the cyclic-code
generated polynomial. Numerous methods have been recently
proposed to solve legal-codes of the cyclic-code generated
polynomial. We think that a better approach for this purpose
is to solve the legal-codes by finding the roots of the cyclic-code
generated polynomial. However, as it is well known, finding
roots of polynomials of high degree in the modulo-q space
GF(q) is very difficult. In this paper we propose a method
to solve the roots of cyclic-code generated polynomial by
using evolutionary computation, which makes use of randomized
searching method from biological natural selection and natural
genetic system. |
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| CS-2 |
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| Title: |
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Intrusion
Detection System Based on a Cooperative Topology Preserving
Method |
| Author(s): |
Emilio Corchado,
Álvaro Herrero,
Bruno Baruque,
José Manuel Saiz |
| Abstract: |
This work describes ongoing multidisciplinary
research which aims to analyse and to apply neural networks
architectures to the interesting field of computer security.
In this paper, we present a novel approach for Intrusion Detection
Systems (IDS) based on an unsupervised connectionist model
used as a method for classifying data. It is used in this
special case, as a method to analyse the traffic which travels
along the analysed network, detecting anomalous traffic patterns
related to SNMP (Simple Network Management Protocol). Once
the data has been collected and pre-processed, we use a novel
connectionist topology preserving model to analyse the traffic
data. This model is an extension of the negative feedback
network characterised by the use of lateral connections on
the output layer. These lateral connections have been derived
from the Rectified Gaussian distribution. |
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| CS-3 |
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| Title: |
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Model Selection for Kernel Based
Intrusion Detection Systems |
| Author(s): |
Srinvas Mukkamala,
A. H. Sung,
B. M. Ribeiro |
| Abstract: |
This paper describes results concerning the
robustness and generalization capabilities of a supervised
machine learning method in detecting intrusions using network
audit trails. We also evaluate the impact of kernel type and
parameter values on the accuracy with which a support vector
machine (SVM) performs intrusion classification. We show that
classification accuracy varies with the kernel type and the
parameter values; thus, with appropriately chosen parameter
values, intrusions can be detected by SVMs with higher accuracy
and lower rates of false alarms. Feature selection is as important
for intrusion detection as it is for many other problems.
We present support vector decision feature selection method
for intrusion detection. It is demonstrated that, with appropriately
chosen features, intrusions can be detected in real time or
near real time. |
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| CS-4 |
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| Title: |
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A comparison of three genetic algorithms
for locking-cache contents selection in real-time systems |
| Author(s): |
E. Tamura,
J.V. Busquets-Mataix,
A. Martí Campoy |
| Abstract: |
Locking caches, providing full determinism and
good performance, are a very interesting solution to replacing
conventional caches in real-time systems. In such systems,
temporal correctness must be guaranteed. The use of predictable
components, like locking caches, helps the system designer
to determine if all the tasks will meet its deadlines. However,
when locking caches are used in a static manner, the system
performance depends on the instructions loaded and locked
in cache. The selection of these instructions may be accomplished
through a genetic algorithm. This paper shows the impact of
the fitness function in the final performance provided by
the real-time system. Three fitness functions have been evaluated,
showing differences in the utilisation and performance obtained. |
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| CS-5 |
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| Title: |
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A Binary Digital Watermarking Scheme
Based On The Orthogonal Vector And ICA-SCS Denoising |
| Author(s): |
Han dongfeng ,
Li wenhui |
| Abstract: |
This paper proposed a new perceptual digital
watermarking scheme based on ICA, SCS, the human visual system
(HVS), discrete wavelet transform (DWT) and the orthogonal
vector. The original gray image first is divided into 8 8
blocks, and then permuted. A 1-level DWT is applied to each
8 8 block. Each watermark bit is modulated by orthogonal vector,
then the watermark is add to the original image. Finally the
IDWT is performed to form the watermarked image. In the watermarking
detection process the independent component analysis (ICA)-based
sparse code shrinkage (SCS) technique is employed to denoise,
and make using of the orthogonal vector character. By hypothetical
testing, the watermark can be extracted exactly. The experimental
results show that the proposed technique successfully survives
image processing operations, image cropping, noise adding
and the JPEG lossy compression. Especially, the scheme is
robust towards image sharping and image enhancement. |
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