A Static Web Immune System and Its Robustness Analysis

A Static Web Immune System and Its Robustness Analysis

Tao Gong (Donghua University, China & Central South University, China)
DOI: 10.4018/978-1-60566-310-4.ch011
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Abstract

Static Web immune system is an important applicatiion of artificial immune system, and it is also a good platform to develop new immune computing techniques. On the Static Web system, a normal model is proposed with the space property and the time property of each component, in order to identify the normal state of the system that the artificial immune system protects. Based on the normal model, the Static Web immune sytsem is modelled with three tiers, that is the innate immune tier, the adaptive immune tier and the parallel immune tier. All the three tiers are inspired from the natural immune system. On the tri-tier immune model, the self detection mechanism is proposed and programmed based on the normal model, and the non-self detection is based on the self detection. Besides, the recognition of known non-selfs and unknown non-selfs are designed and analyzed. It is showed that the Static Web immune system is effective and useful for both theory and applications.
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A.2 Background

Web system is popular on the Internet now and useful for many web users, and web security has become a serious problem due to viruses, worms and faults (Balthrop, Forrest & Newman, et al., 2004; Orman, 2003). To solve the security problem, some detecting techniques are used to recognize the non-selfs such as viruses and faults by matching the features of the non-selfs, but the traditional techniques have a difficult bottleneck in detecting unknown non-selfs especially such as brand-new viruses. To overcome the bottleneck, a new strategy for detecting the unknown non-selfs has been proposed with the normal model of the system that the artificial immune system protects. Current work has been done on the static web system and in fact many static web systems are useful and popular on the Internet, such as the webpage system for many companies and universities.

A.2.1 Space Property of Component

Suppose a static web system S is comprised of m web directories and n files in the cyberspace, and the system can be represented with the set

.

Here, pij denotes the jth file in the ith directory of the system S, dk denotes the kth directory in the system S, and ni denotes the sum of all files in the ith directory of the system S.

The components of the static web system are software parts, and the software is used to simulate the physical world in the cyberspace. In the physical world, every object has unique 3-dimension space coordinates and 1-dimension time coordinate, so that the state of the object is uniquely identified by its space-time coordinates (Einstein, 1920). Alike in the cyberspace, every software part has unique location for storing the space property because the storage of the software is based on the hardware in the physical world. The absolute pathname pi is used to represent the location information for storing the file and/or the directory, and the pathname consists of the name ri of the disk or the URL, the name di of the directory and the full name ni of the file ci, shown in Figure 1. The full name of the file includes the file-name of the file and the suffix name of the file, and the suffix name of the file is one of features that are useful for classifying the files.

Figure 1.

3-dimension information of the absolute pathname for files. ©2008 Tao Gong. Used with permission.

According to the basic rules of the operating systems for managing the files, the absolute pathname of the file ci uniquely identifies the location of the file in the computer. One absolute pathname belongs to only one file at a certain time, and at that time the file has only one absolute pathname.

Key Terms in this Chapter

Self Database: The database that stores the space-time information of the selfs is called as the self database.

Parallel Immune Tier: The immune computing tier, which uses parallel computing to increase efficiency and load balance of immune computation, is called as the parallel immune tier of the artificial immune system.

Innate Immune Tier: The immune computing tier, which detects the selfs & non-selfs and recognize all the known non-selfs, is called as the innate immune tier of the artificial immue system.

Probability for Detecting Non-Selfs: The measurement on the probability of the random event that the artificial immune system detects the non-selfs is called as the probability for detecting the non-selfs.

Non-Self Database: The database that stores the feature information of the known non-selfs is called as the non-self database.

Self/Non-Self Detection: The process for detecting the object to decide whether the object is a self or non-self is called as the self/non-self detection.

Adaptive Immune Tier: The immune computing tier, which learn and recognize the unknown non-selfs, is called as the adaptive immune tier of the artificial immune system.

Probability for Learning Unknown Non-Selfs: The measurement on the probability of the random event that the artificial immune system learns the unknown non-selfs is called as the probability for learning the unknown non-selfs.

Normal Model of Normal Static Web System: The set of space-time properties for all the normal components of the normal static web system is called as the normal model of the normal static web system.

Immune Memorization: The process for remembering the unknown non-selfs to transform the non-self into the known ones is called as the immune memorization.

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Table of Contents
Foreword
Lipo Wang
Preface
Hongwei Mo
Chapter 1
Fabio Freschi, Carlos A. Coello Coello, Maurizio Repetto
This chapter aims to review the state of the art in algorithms of multiobjective optimization with artificial immune systems (MOAIS). As it will be... Sample PDF
Multiobjective Optimization and Artificial Immune Systems: A Review
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Chapter 2
Jun Chen, Mahdi Mahfouf
The primary objective of this chapter is to introduce Artificial Immune Systems (AIS) as a relatively new bio-inspired optimization technique and to... Sample PDF
Artificial Immune Systems as a Bio-Inspired Optimization Technique and Its Engineering Applications
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Chapter 3
Licheng Jiao, Maoguo Gong, Wenping Ma
Many immue-inspired algorithms are based on the abstractions of one or several immunology theories, such as clonal selection, negative selection... Sample PDF
An Artificial Immune Dynamical System for Optimization
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Chapter 4
Malgorzata Lucinska, Slawomir T. Wierzchon
Multi-agent systems (MAS), consist of a number of autonomous agents, which interact with one-another. To make such interactions successful, they... Sample PDF
An Immune Inspired Algorithm for Learning Strategies in a Pursuit-Evasion Game
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Chapter 5
Luis Fernando Niño Vasquez, Fredy Fernando Muñoz Mopan, Camilo Eduardo Prieto Salazar, José Guillermo Guarnizo Marín
Artificial Immune Systems (AIS) have been widely used in different fields such as robotics, computer science, and multi-agent systems with high... Sample PDF
Applications of Artificial Immune Systems in Agents
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Chapter 6
Xingquan Zuo
Inspired from the robust control principle, a robust scheduling method is proposed to solve uncertain scheduling problems. The uncertain scheduling... Sample PDF
An Immune Algorithm Based Robust Scheduling Methods
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Chapter 7
Fabio Freschi, Maurizio Repetto
The increasing cost of energy and the introduction of micro-generation facilities and the changes in energy production systems require new... Sample PDF
Artificial Immune System in the Management of Complex Small Scale Cogeneration Systems
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Chapter 8
Krzysztof Ciesielski, Mieczyslaw A. Klopotek, Slawomir T. Wierzchon
In this chapter the authors discuss an application of an immune-based algorithm for extraction and visualization of clusters structure in large... Sample PDF
Applying the Immunological Network Concept to Clustering Document Collections
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Chapter 9
Xiangrong Zhang, Fang Liu
The problem of feature selection is fundamental in various tasks like classification, data mining, image processing, conceptual learning, and so on.... Sample PDF
Feature Selection Based on Clonal Selection Algorithm: Evaluation and Application
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Chapter 10
Yong-Sheng Ding, Xiang-Feng Zhang, Li-Hong Ren
Future Internet should be capable of extensibility, survivability, mobility, and adaptability to the changes of different users and network... Sample PDF
Immune Based Bio-Network Architecture and its Simulation Platform for Future Internet
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Chapter 11
Tao Gong
Static Web immune system is an important applicatiion of artificial immune system, and it is also a good platform to develop new immune computing... Sample PDF
A Static Web Immune System and Its Robustness Analysis
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Chapter 12
Alexander O. Tarakanov
Based on mathematical models of immunocomputing, this chapter describes an approach to spatio-temporal forecast (STF) by intelligent signal... Sample PDF
Immunocomputing for Spatio-Temporal Forecast
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Chapter 13
Fu Dongmei
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Research of Immune Controllers
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Chapter 14
Xiaojun Bi
In fact, image segmentation can be regarded as a constrained optimization problem, and a series of optimization strategies can be used to complete... Sample PDF
Immune Programming Applications in Image Segmentation
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Chapter 15
Xin Wang, Wenjian Luo, Zhifang Li, Xufa Wang
A hardware immune system for the error detection of MC8051 IP core is designed in this chapter. The binary string to be detected by the hardware... Sample PDF
A Hardware Immune System for MC8051 IP Core
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Chapter 16
Mark Burgin, Eugene Eberbach
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Chapter 17
Terrence P. Fries
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Chapter 18
Konstantinos Konstantinidis, Georgios Ch. Sirakoulis, Ioannis Andreadis
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Ant Colony Optimization for Use in Content Based Image Retrieval
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Chapter 19
Miroslav Bursa, Lenka Lhotska
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Ant Colonies and Data Mining
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Chapter 20
Bo-Suk Yang
This chapter describes a hybrid artificial life optimization algorithm (ALRT) based on emergent colonization to compute the solutions of global... Sample PDF
Artificial Life Optimization Algorithm and Applications
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Chapter 21
Martin Macaš, Lenka Lhotská
A novel binary optimization technique is introduced called Social Impact Theory based Optimizer (SITO), which is based on social psychology model of... Sample PDF
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Chapter 22
James F. Peters, Shabnam Shahfar
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Chapter 23
Dingju Zhu
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Chapter 24
Tang Mo, Wang Kejun, Zhang Jianmin, Zheng Liying
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