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Service specific anomaly detection for network intrusion detection

Published: 11 March 2002 Publication History

Abstract

The constant increase of attacks against networks and their resources (as recently shown by the CodeRed worm) causes a necessity to protect these valuable assets. Firewalls are now a common installation to repel intrusion attempts in the first place. Intrusion detection systems (IDS), which try to detect malicious activities instead of preventing them, offer additional protection when the first defense perimeter has been penetrated. ID systems attempt to pin down attacks by comparing collected data to predefined signatures known to be malicious (signature based) or to a model of legal behavior (anomaly based).Anomaly based systems have the advantage of being able to detect previously unknown attacks but they suffer from the difficulty to build a solid model of acceptable behavior and the high number of alarms caused by unusual but authorized activities. We present an approach that utilizes application specific knowledge of the network services that should be protected. This information helps to extend current, simple network traffic models to form an application model that allows to detect malicious content hidden in single network packets. We describe the features of our proposed model and present experimental data that underlines the efficiency of our systems.

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cover image ACM Conferences
SAC '02: Proceedings of the 2002 ACM symposium on Applied computing
March 2002
1200 pages
ISBN:1581134452
DOI:10.1145/508791
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 March 2002

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Author Tags

  1. anomaly eetection
  2. intrusion eetection
  3. network security

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SAC02
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SAC02: 2002 ACM Symposium on Applied Computing
March 11 - 14, 2002
Madrid, Spain

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Overall Acceptance Rate 1,650 of 6,669 submissions, 25%

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  • (2024)Fuzzy anomaly scores for Isolation ForestApplied Soft Computing10.1016/j.asoc.2024.112193166(112193)Online publication date: Nov-2024
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