SecureDIS: a Framework for SecureDIS: a Framework for Secure Data Integration Secure Data Integration

SystemsSystems

Fatimah Akeelfya1g12@soton.ac.uk

Supervisors: Dr. Gary B. Wills & Dr. Andrew Gravell

School of Electronics and Computer Science, ESS Group

2

Katrina

SARS

The use of intensive amount of data creates the so calleddata integration systems

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A Scenario of Data Integration System (DIS)A Scenario of Data Integration System (DIS)

System Security Management (SSM)

Data Integrator (DI)

Media DS3

Integration Approach(IA)

NHSDS1

ONSDS2

Social Networks

DS4

Data Integration Application

Data SourcesData Sources

Unintentional disclosure of private information caused by system design.

4System Security Management (SSM)

Data Integrator (DI)

Media DS3

Integration Approach(IA)

NHSDS1

ONSDS2

Social Networks

DS4

Data Integration Application

Data SourcesData Sources

SecuritySecurity

PrivacyPrivacy

TrustTrust

5

66

1 2

Build a DIS to be secure by design

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Focus on disclosure of private data

The Goal is to:

Create a secure and reliable DIS

that Produce accurate results,

used in decision making and disaster recovery.

Which is achieved by having

security requirements propagate through the development

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Data Sources (DS)

Integration Approach (IA) Data Integrator (DI)

System Security Management (SSM)

Secure Data Integration Systems (SecureDIS)

Security

Trust Privacy

Data Consumers (DC)

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Completed

Published

M. Lenzerini, “Data integration: A theoretical perspective,” in Proceedings of the 21st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 2002, pp. 233–246.

A. Calì, D. Calvanese, G. D. Giacomo, and M. Lenzerini, “Data integration under integrity constraints,” Adv. Inf. Syst. Eng., pp. 262–279, 2006.

C. Clifton, M. Kantarcioǧlu, A. Doan, G. Schadow, J. Vaidya, A. Elmagarmid, and D. Suciu, “Privacy-preserving data integration and sharing,” in Proceedings of the 9th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery - DMKD ’04, 2004, p. 19.

K. Pasierb, T. Kajdanowicz, and P. Kazienko, “Privacy-preserving data mining, sharing and publishing,” J. Med. Informatics Technol., vol. 18, 2011.

M. Haddad, M.-S. Hacid, and R. Laurini, “Data Integration in Presence of Authorization Policies,” in 2012 IEEE 11th International Conference on Trust, Security and Privacy in Computing and Communications, 2012, pp. 92–99.

S. W. Van Den Braak, S. Choenni, R. Meijer, and A. Zuiderwijk, “Trusted third parties for secure and privacy-preserving data integration and sharing in the public sector,” in Proceedings of the 13th Annual International Conference on Digital Government Research - dg.o ’12, 2012, pp. 135 –144.

A. Morton and M. Sasse, “Privacy is a process, not a PET: a theory for effective privacy practice,” in Proceedings of the 2012 workshop on New security paradigms, 2012, pp. 87–104.

S. S. Bhowmick, L. Gruenwald, M. Iwaihara, and S. Chatvichienchai, “PRIVATE-IYE: A Framework for Privacy Preserving Data Integration,” in 22nd International Conference on Data Engineering Workshops (ICDEW’06), 2006, pp. 91–91.

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Questions & Comments?Questions & Comments?

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