AIS for Misbehavior Detection in Wireless Sensor Networks: Performance and Design Principles

A sensor network is a collection of wireless devices that are able to monitor physical or environmental conditions. These devices (nodes) are expected to operate autonomously, be battery powered and have very limited computational capabilities. This makes the task of protecting a sensor network against misbehavior or possible malfunction a challenging problem. In this document we discuss performance of Artificial immune systems (AIS) when used as the mechanism for detecting misbehavior. We show that (i) mechanism of the AIS have to be carefully applied in order to avoid security weaknesses, (ii) the choice of genes and their interaction have a profound influence on the performance of the AIS, (iii) randomly created detectors do not comply with limitations imposed by communications protocols and (iv) the data traffic pattern seems not to impact significantly the overall performance. We identified a specific MAC layer based gene that showed to be especially useful for detection; genes measure a network's performance from a node's viewpoint. Furthermore, we identified an interesting complementarity property of genes; this property exploits the local nature of sensor networks and moves the burden of excessive communication from normally behaving nodes to misbehaving nodes. These results have a direct impact on the design of AIS for sensor networks and on engineering of sensor networks.Comment: 16 pages, 20 figures, a full version of our IEEE CEC 2007 pape

Scheduling of offshore wind farm installation using simulated annealing

This paper focuses on the scheduling problem in the offshore wind farm installation process, which is strongly influenced by the offshore weather condition. Due to the nature of the offshore weather condition, i.e., partially predictable and uncontrollable, it is urgent to find a way to schedule the offshore installation process effectively and economically. For this purpose, this work presents a model based on Timed Petri Nets (TPN) approach for the offshore installation process and applies simulated annealing algorithm to find the optimal schedule

Artificial immune systems: Survey and applications in ad hoc wireless networks

artificial immune system. This document reviews recent efforts in the area of Artificial immune systems (AIS) and their applications for (ad hoc) wireless networks. It presents basic mechanism of Human immune systems, introduces the reader to the learning paradigms of AIS, sums up misbehavior in ad hoc wireless networks and discusses pros and cons of AIS in increasing robustness of ad hoc wireless networks against misbehavior

Is AIS Based Misbehavior Detection Suitable for Wireless Sensor Networks

Abstract — Sensor networks are a flavor of ad hoc wireless networks with limited computational capabilities. The task to protect such networks against misbehavior is therefore more complicated as any detection mechanism has to be simple and efficient. We employed mechanisms based on Artificial immune systems (AIS) in order to detect misbehavior. We conclude that AIS based misbehavior detection offers a decent detection performance at a very low computational cost. We show that misbehavior detection when applied at both the MAC and network layers may still not be sufficient, instead it will be necessary to extend it to layers with end-to-end connection information; this would also allow for classifying misbehavior by its potential to cause harm. These results have a direct impact on the design of AIS for sensor networks and on engineering of sensor networks. I