Danger Theory: The Link between AIS and IDS?

A survey of artificial immune system based intrusion detection

In the area of computer security, Intrusion Detection (ID) is a mechanism that attempts to discover abnormal access to computers by analyzing various interactions. There is a lot of literature about ID, but this study only surveys the approaches based on Artificial Immune System (AIS). The use of AIS in ID is an appealing concept in current techniques. This paper summarizes AIS based ID methods from a new view point; moreover, a framework is proposed for the design of AIS based ID Systems (IDSs). This framework is analyzed and discussed based on three core aspects: antibody/antigen encoding, generation algorithm, and evolution mode. Then we collate the commonly used algorithms, their implementation characteristics, and the development of IDSs into this framework. Finally, some of the future challenges in this area are also highlighted.

A systems biology perspective on plant-microbe interactions: biochemical and structural targets of pathogen effectors

Plants have biochemical defences against stresses from predators, parasites and pathogens. In this review we discuss the interaction of plant defences with microbial pathogens such as bacteria, fungi and oomycetes, and viruses. We examine principles of complex dynamic networks that allow identification of network components that are differentially and predictably sensitive to perturbation, thus making them likely effector targets. We relate these principles to recent developments in our understanding of known effector targets in plant-pathogen systems, and propose a systems-level framework for the interpretation and modelling of host-microbe interactions mediated by effectors. We describe this framework briefly, and conclude by discussing useful experimental approaches for populating this framework.