Abstract
The Next Generation mobile network expected to be fully automated to meet the growing need for data rates and quality in communication. These prodigious demands have also increased the amount of data being handled in these wireless networks. The cellular networks can leverage vital data about the user and the network conditions providing all-inclusive visibility and intelligence in communication. Emerging analytic technologies such as big data and neural networks have been used to unearth vital insight from network traffic to assist intelligent models in routing packets. Reactive protocols are an emerging model in the intelligent routing of traffic in ad-hoc networks. In this paper, we first utilize the reactive protocols to route traffic in a wireless network while analyzing anomalous behavior. In the case of anomaly detection in wireless communication, combined performance indicators to identify outliers. The detected outliers been compared with the ground data and routes created using the reactive protocols. The combination of reactive protocols and the key performance indicators in network performance uncovered anomalies leading to segregation of these traffic in routing. From the results, it is evident that an abrupt surge in the traffic indicated an anomaly and identify the areas of interest in a network especially for resource and path allocation and fault avoidance. A MATLAB GUI was used to simulate the reactive protocols for routing of traffic and generation of data sets that analyze in Microsoft Excel to characterize the key performance indicators of the network.
Highlights
The continuous growth in mobile technology leading to faster data rates and the increase in sensitive information has led to most service in base stations to be targets of malicious attacks
The need for user profiling and authentication is based on the fact that most attacks on cellular networks are based on software flaws and design errors that can be combined to provide a malicious door to the system, for instance, the recent cloning of GSM cards [3]
The local database (VLR) and mobile switching center (MSC) are distributed to serve localized regions which are divided into local areas (LA) that are further divided into cells [4]
Summary
The continuous growth in mobile technology leading to faster data rates and the increase in sensitive information has led to most service in base stations to be targets of malicious attacks. The need for user profiling and authentication is based on the fact that most attacks on cellular networks are based on software flaws and design errors that can be combined to provide a malicious door to the system, for instance, the recent cloning of GSM cards [3]. These incidents have made it vital to develop countermeasures such as they normally detection that is reliant on the profiling of the network users. Simulated the user traffic using a MATLAB GUI to obtain the necessary data set for principal performance indicators analysis to detect the outlier in the network
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