Generalization Privacy Protection Method for Alarm Data

Dong Sheng Zhang

doi:10.4028/www.scientific.net/AMM.543-547.3646

Paper Titles

Research on Parallel Association Rules Mining Algorithm Based on Hadoop
p.3625

Shamir's Threshold Scheme to Ensure Security in Cloud Computing Services
p.3632

Research of Edge Centrality Based on the Algebraic Connectivity
p.3636

The Grid Task Attemper Layer Model Based on Agent Role
p.3641

Generalization Privacy Protection Method for Alarm Data
p.3646

Simulation and Algorithm of Network Public Opinion Based on a New Wavelet Threshold
p.3650

A Multiple Ring Fast Computing Method Based on MapReduce in Digraph
p.3655

Research of the Tourism Marketing Basing on the Data Mining
p.3659

Research on Tourism E-Commerce Based on Web Data Mining Technology
p.3663

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 543-547Generalization Privacy Protection Method for Alarm...

Generalization Privacy Protection Method for Alarm Data

Abstract:

To resolve conflicts between share and collaborative analysis requirements of security alarm and alert data holders worries about privacy, it firstly probes into the anonymized protection method Incognito. Based on that, it improves the algorithm to solve existing problems by extending common data like privacy protection targets to alert data. The generalized anonymous processing model for alert data is developed and the quantitative evaluation is realized between the level of alert datas secret protection and data quality. With authoritative data set of intrusion detection attack scenario as test data, the experiment validates efficiency and effectiveness of the proposed method on the part of performance and security.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 543-547)

Pages:

3646-3649

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.543-547.3646

Citation:

Cite this paper

Online since:

March 2014

Authors:

Dong Sheng Zhang*

Keywords:

Alarm Correlation, Incognito Algorithm, Network Security, Privacy Protection, Safety Evaluation

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] X. Yin, K. Lakkaraju, Y. Li et al. Selecting log data sources to correlate attack traces for computer network security: Preliminary results. In: Proceedings of the 11th International Conference on Telecommunication Systems, Modelling and Analysis, 2003: 112-116.

Google Scholar

[2] T. Limmer, and F. Dressler. Survey of Event Correlation Techniques for Attack Detection in Early Warning Systems. University of Erlangen, Dept. of Computer Science, Technical Report, 2008: 45-50.

Google Scholar

[3] L. H. Cox. Suppression methodology and statistical disclosure control. Journal of the American Statistical Association, 2004: 377-385.

Google Scholar

[4] B. Fung, K. Wang, R. Chen et al. Privacy-preserving data publishing: a survey of recent developments. ACM Computing Surveys (CSUR). 2010: 234-240.

DOI: 10.1145/1749603.1749605

Google Scholar

[5] A. Meyerson, and R. Williams. On the complexity of optimal k-anonymity. In: Proceedings of the 23th ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, 2004: 223-228.

DOI: 10.1145/1055558.1055591

Google Scholar