loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Paola Baldassarri ; Anna Montesanto and Paolo Puliti

Affiliation: Polytechnic University of Marche, Italy

Keyword(s): Intrusion Detection System, Anomaly Detection, Statistical processing, Self-Organizing Maps.

Related Ontology Subjects/Areas/Topics: Information and Systems Security ; Intrusion Detection & Prevention

Abstract: The main idea of the present work is to create a system able to detect intrusions in computer networks. For this purpose we propose a novel intrusion detection system (IDS) based on an anomaly approach. We analyzed the network traffic from (outbound traffic) and towards (inbound traffic) a victim host through another host. Besides we realized an architecture consisted of two subsystems: a statistical subsystem and a neural networks based subsystem. The first elaborates chosen features extracted from the network traffic and it allows determining if an attack occurs through a preliminary visual inspection. The neural subsystem receives in input the output of the statistical subsystem and it has to indicate the status of the monitored host. It classifies the network traffic distinguishing the background traffic from the anomalous one. Moreover the system has to be able to classify different instances of the same attack in the same class, distinguishing in a completely autonomous way dif ferent typology of attack. (More)

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 18.116.51.117

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Baldassarri, P.; Montesanto, A. and Puliti, P. (2007). DETECTING ANOMALOUS TRAFFIC USING STATISTICAL PROCESSING AND SELF-ORGANIZING MAPS. In Proceedings of the Second International Conference on Security and Cryptography (ICETE 2007) - SECRYPT; ISBN 978-989-8111-12-8; ISSN 2184-3236, SciTePress, pages 74-79. DOI: 10.5220/0002123500740079

@conference{secrypt07,
author={Paola Baldassarri. and Anna Montesanto. and Paolo Puliti.},
title={DETECTING ANOMALOUS TRAFFIC USING STATISTICAL PROCESSING AND SELF-ORGANIZING MAPS},
booktitle={Proceedings of the Second International Conference on Security and Cryptography (ICETE 2007) - SECRYPT},
year={2007},
pages={74-79},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002123500740079},
isbn={978-989-8111-12-8},
issn={2184-3236},
}

TY - CONF

JO - Proceedings of the Second International Conference on Security and Cryptography (ICETE 2007) - SECRYPT
TI - DETECTING ANOMALOUS TRAFFIC USING STATISTICAL PROCESSING AND SELF-ORGANIZING MAPS
SN - 978-989-8111-12-8
IS - 2184-3236
AU - Baldassarri, P.
AU - Montesanto, A.
AU - Puliti, P.
PY - 2007
SP - 74
EP - 79
DO - 10.5220/0002123500740079
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic