MANET Mining: Mining Association Rules

Abstract

The growing advances in mobile devices, processing power, display and storage capabilities, together with competitive market has enabled information technology to be more affordable and available to almost everybody around the world. Moreover, with the advent of wireless communications and mobile computing, another type of wireless communications, called Mobile Ad hoc NETworks (MANETs), came into existence. The operation of MANET does not depend on pre-existence infrastructure or base stations, since there is no central node in the network and nodes collaboratively share all the network activities. The simplicity of MANET deployment comes with a cost of complexity of the algorithms in different layers. In addition, the absence of the infrastructure induces new challenges to wireless networks in the fields of routing, security, power conservation, quality of service, and so on. For better perception of the new concepts in this chapter, a summary of the necessary background in Data Mining (DM) is given, and particularly more emphasis and in depth explanation is given on association rule mining technique, an area upon which the new concepts of this chapter revolves. DM or Knowledge Discovery in Databases (KDD) is defined as “The nontrivial extraction of implicit, previously unknown, and potentially useful information from data” (Frawley et al., 1992). DM is the process of finding hidden relationships in data sets and summarizing these patterns in models. These patterns can be utilized to understand the whole data sets. In simplified terms, DM is a technology that allows an applicant to discover knowledge, which is hidden in large data sets, by applying various algorithms (Hofmann, 2003). This chapter shows how DM approaches are applied to MANET, in that the traffic of MANET is mined in a simple way called “MANET Mining using Association Rule Techniques”. MANET Mining enables the establishment of the fact that there are still some hidden relationships (patterns) amongst routing nodes, even though nodes are independent of each other. These relationships may be used to provide useful information to different MANET protocols in different layers. Precisely, MANET Mining, discovers hidden patterns (meta-data) in the third layer to be used as common tokens (keys) in the application layer in a bid to address one challenging security problem in MANET, namely, key distribution. This is the first time this approach has been used to solve key distribution problem in MANET. Interestingly, security in MANET has been paid a lot of attention over the past few years. One of the most challenging security issue in MANET is key management where there is no on-line access to trusted authorities. Key management is the central part of any secure communication, and is the weak point of system security and protocol design. Most 15