Home // SECURWARE 2014, The Eighth International Conference on Emerging Security Information, Systems and Technologies // View article
Authors:
Paulo R. G. Hernandes Jr.
Luiz F. Carvalho
Gilberto Fernandes Jr.
Mario L. Proença Jr.
Keywords: Characterization; Traffic Monitoring; Network Management; Genetic Algorithm, sFlow
Abstract:
Every day computer networks have more significance in our lives, and these network’s complexity is still growing. To help customers achieve maximum productivity and avoid security risks, network administrators have to manage network resources efficiently. Traffic monitoring is an important task, which describes the network’s normal behavior. Thereby, we present a Digital Signature of Network Segment using Flow Analysis (DSNSF) as a mechanism to assist network management and information security through traffic characterization. Our new approach uses a genetic algorithm to optimize the process. In order to accomplish this task, we compared the novel model with another similar method, Ant Colony Optimization for Digital Signature (ACODS), using a real data set of traffic for bits and packets. We also evaluate these models to measure their accuracy.
Pages: 62 to 67
Copyright: Copyright (c) IARIA, 2014
Publication date: November 16, 2014
Published in: conference
ISSN: 2162-2116
ISBN: 978-1-61208-376-6
Location: Lisbon, Portugal
Dates: from November 16, 2014 to November 20, 2014