research-article

Relationships between information security metrics: an empirical study

Authors:

Rodrigo Sanches Miani,

Michel Cukier,

Bruno Bogaz Zarpelão,

Leonardo de Souza MendesAuthors Info & Claims

CSIIRW '13: Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop

Article No.: 22, Pages 1 - 4

https://doi.org/10.1145/2459976.2460002

Published: 08 January 2013 Publication History

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Abstract

Finding relevant metrics in information security is an important but difficult problem. In this paper, we propose to empirically investigate the relevance of different security metrics that could be derived from intrusion prevention system (IPS) alert events and computer security incident data. Based on the data provided by the University of Maryland, we show that IPS metrics are linked to security incidents, and also that different types of security incidents have different significant metrics. These results can be used for identifying possible candidates for security incident indicators, developing methods to improve incident prevention and helping organizations interpret their IPS's better in the future.

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Cited By

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Billard A(2019)Decision Model for the Security and Utility Risk Evaluation (SURE) FrameworkProceedings of the Australasian Computer Science Week Multiconference10.1145/3290688.3290694(1-11)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3290688.3290694
Miani RZarpelao BSobesto BCukier M(2015)A Practical Experience on Evaluating Intrusion Prevention System Event Data as Indicators of Security IssuesProceedings of the 2015 IEEE 34th Symposium on Reliable Distributed Systems (SRDS)10.1109/SRDS.2015.17(296-305)Online publication date: 28-Sep-2015
https://dl.acm.org/doi/10.1109/SRDS.2015.17
Puys MRivière LBringer JLe T(2015)High-Level Simulation for Multiple Fault Injection EvaluationData Privacy Management, Autonomous Spontaneous Security, and Security Assurance10.1007/978-3-319-17016-9_19(293-308)Online publication date: 28-Mar-2015
https://doi.org/10.1007/978-3-319-17016-9_19

Index Terms

Relationships between information security metrics: an empirical study
1. Security and privacy
2. Social and professional topics
  1. Computing / technology policy
    1. Computer crime

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Published In

CSIIRW '13: Proceedings of the Eighth Annual Cyber Security and Information Intelligence Research Workshop

January 2013

282 pages

ISBN:9781450316873

DOI:10.1145/2459976

Editors:
Frederick Sheldon
Oak Ridge National Laboratory
,
Annarita Giani
Los Alamos National Laboratory
,
Axel Krings
University of Idaho
,
Robert Abercrombie
Oak Ridge National Laboratory

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 January 2013

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Fundação de Amparo à Pesquisa do Estado de São Paulo

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CSIIRW '13

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Los Alamos National Labs
Sandia National Labs
DOE
Lawrence Livermore National Lab.
BERKELEYLAB
Argonne Natl Lab
Idaho National Lab.
Nevada National Security Site

CSIIRW '13: Cyber Security and Information Intelligence

January 8 - 10, 2013

Tennessee, Oak Ridge, USA

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Billard A(2019)Decision Model for the Security and Utility Risk Evaluation (SURE) FrameworkProceedings of the Australasian Computer Science Week Multiconference10.1145/3290688.3290694(1-11)Online publication date: 29-Jan-2019
https://dl.acm.org/doi/10.1145/3290688.3290694
Miani RZarpelao BSobesto BCukier M(2015)A Practical Experience on Evaluating Intrusion Prevention System Event Data as Indicators of Security IssuesProceedings of the 2015 IEEE 34th Symposium on Reliable Distributed Systems (SRDS)10.1109/SRDS.2015.17(296-305)Online publication date: 28-Sep-2015
https://dl.acm.org/doi/10.1109/SRDS.2015.17
Puys MRivière LBringer JLe T(2015)High-Level Simulation for Multiple Fault Injection EvaluationData Privacy Management, Autonomous Spontaneous Security, and Security Assurance10.1007/978-3-319-17016-9_19(293-308)Online publication date: 28-Mar-2015
https://doi.org/10.1007/978-3-319-17016-9_19

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A Survey on Systems Security Metrics

Designing Sound Security Metrics

Security metrics for source code structures

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