A Review of Artificial Immune System Based Security Frameworks for MANET <s> Danger Theory Based <s> For over 50 years immunologists have based their thoughts, experiments, and clinical treatments on the idea that the immune system functions by making a distinction between self and nonself. Although this paradigm has often served us well, years of detailed examination have revealed a number of inherent problems. This Viewpoint outlines a model of immunity based on the idea that the immune system is more concerned with entities that do damage than with those that are foreign. <s> BIB001 </s> A Review of Artificial Immune System Based Security Frameworks for MANET <s> Danger Theory Based <s> The natural immune system exhibits many properties that are of interest to the area of web mining. Of particular ::: interest is the dynamic nature of the immune system when compared with the dynamic nature of mining ::: information from the web. As part of a larger project to construct a large-scale dynamic web-mining system, this ::: chapter reports initial work on constructing an E-mail classifier system. The Artificial Immune System for Email ::: Classification (AISEC) is described in detail and compared with a traditional approach of naive Bayesian ::: classification. Results reported compare favorably with the Bayesian approach and this chapter highlights how ::: the Danger Theory from immunology can be used to further improve the performance of such an artificial ::: immune system. <s> BIB002 </s> A Review of Artificial Immune System Based Security Frameworks for MANET <s> Danger Theory Based <s> Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems. <s> BIB003 </s> A Review of Artificial Immune System Based Security Frameworks for MANET <s> Danger Theory Based <s> Artificial Immune Systems (AIS) have been successfully modeled and implemented in several engineering applications. In this work, a goalkeeper strategy in robot soccer based on Danger Theory is proposed. Danger Theory is a recent immune theory which has not been widely applied so far. The proposed strategy is implemented and evaluated using middle league SIMUROSOT from FIRA. Experiments carried out yielded promising results. <s> BIB004 </s> A Review of Artificial Immune System Based Security Frameworks for MANET <s> Danger Theory Based <s> INTRODUCTION ::: ::: In recent years computer systems have become increasingly complex and consequently the challenge of protecting these systems has become ::: increasingly difficult. Various techniques have been implemented to counteract the misuse of computer systems in the form of firewalls, antivirus software and intrusion detection systems. The complexity of networks and dynamic nature of computer systems leaves current methods with significant room for improvement. ::: ::: Computer scientists have recently drawn inspiration from mechanisms found in biological systems and, in the context of computer security, ::: ::: have focused on the human immune system (HIS). The human immune system provides an example of a robust, distributed system that provides a high ::: level of protection from constant attacks. By examining the precise mechanisms of the human immune system, it is hoped the paradigm will ::: improve the performance of real intrusion detection systems. ::: ::: This paper presents an introduction to recent developments in the field of immunology. It discusses the incorporation of a novel immunological paradigm, Danger Theory, and how this concept is inspiring artificial immune systems (AIS). Applications within the context of computer security are outlined drawing direct reference to the underlying principles of Danger Theory and finally, the current state of intrusion detection systems is discussed and improvements suggested. <s> BIB005
Matzinger, the chief advocate of Danger Theory, proposed this theory in 2002 BIB001 and highlighted that the "foreignness" of a microbe is not the main factor that ignites a response and "selfness" is no assurance of tolerance. The fundamental idea in Danger Theory states that antigen presenting cells are triggered by danger/alarm signals from sore cells. Danger signals will not be sent by healthy cells or by cells experiencing normal cell death. Any cell that dies an unnatural death sends out a danger signal and antigens near the dying cell are seized by antigen presenting cells like macrophages and are then presented to the lymphocytes. B-cells also secrete antibodies that match the antigens. The antibodies that match the antigens present in the danger zone will be activated and undergo clonal expansion. Those antibodies that do not match will not be in the danger zone and therefore will not be stimulated. The Two-Signal Model extended by Bretscher et al.  explains Danger Theory in a different way where two signals are needed to activate the lymphocytes: 1) antigen recognition; and 2) co-stimulation. Signal 2 indicates that the antigen is threatening. The Danger Theory has its own disadvantages and Aickelin et al. BIB003 proposed applications of Danger Theory that highlight: • The presence of an APC is required to present a danger signal. • A danger signal does not have to be dangerous. • Danger signals can be positive or negative (presence or absence of signal). • An estimate of nearness may be used to imitate the danger zone. Conceptual ideas were also proposed on how the Danger Theory can be used for anomaly detection. Based on the Danger Theory, an immune response is always sparked by danger signals. Low or high memory usage, fraudulent disk activity and so forth could indicate danger signals. The Immune System can react to the antigens in the danger zone once a danger signal is produced. After the dangerous components are identified they are then sent to a special part of the system for further verification. Another application of the Danger Theory used in intrusion detection can be found in BIB005 . Danger Theory has been applied to data mining problems BIB003 . Consider the case where a user is browsing a set of documents where each document has a set of attributes. When AIS is implemented the antibodies in the system are used to detect the attributes. Each document browsed by the user will be dispensed to the antibodies. When the user expresses interest in the present document a danger signal is raised and antibodies matching the antigen (attribute in the present document) are triggered and become effecters. Wearisome document attributes will endure the auto reactive antibodies. Finally AIS, learns to become a good filter when searching for enthralling documents. Prieto et al. BIB004 used a goalkeeper strategy in the Danger Theory Algorithm (DTAL) that takes into account danger signals, lymphocytes and the danger zone. This technique was used in robot soccer, when the ball is on the source side (tissue) an alarm signal (Signal 1) will be triggered. When the ball (antigen) is taken by the opponent to the penalty side (danger zone) Signal 2 will be triggered. When both signals are received the lymphocyte is actuated to clear the ball. This strategy showed a performance above 90%. The work in BIB002 highlighted an application of Danger Theory to accentuate the effectiveness of an e-mail classifier system. In web-mining usage of various types of media may cause various signals to be released but in an e-mail system an abnormal email may release a "fascinating" signal of one category. The strong pertinence of these features constitutes a form of the Danger Theory.