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Preventing unauthorized data flows

Uzun, Emre, Parlato, Gennaro, Atluri, Vijayalakshmi, Ferrara, Anna Lisa, Vaidya, Jaideep, Sural, Shamik and Lorenzi, David, (2017) Preventing unauthorized data flows Livraga, G. and Zhu, S. (eds.) In Data and Applications Security and Privacy XXXI. DBSec 2017. vol. 10359, Springer. 0 pp, pp. 41-62. (doi:10.1007/978-3-319-61176-1_3).

Record type: Conference or Workshop Item (Paper)


Trojan Horse attacks can lead to unauthorized data flows and can cause either a confidentiality violation or an integrity violation. Existing solutions to address this problem employ analysis techniques that keep track of all subject accesses to objects, and hence can be expensive. In this paper we show that for an unauthorized flow to exist in an access control matrix, a flow of length one must exist. Thus, to eliminate unauthorized flows, it is sufficient to remove all one-step flows, thereby avoiding the need for expensive transitive closure computations. This new insight allows us to develop an efficient methodology to identify and prevent all unauthorized flows leading to confidentiality and integrity violations. We develop separate solutions for two different environments that occur in real life, and experimentally validate the efficiency and restrictiveness of the proposed approaches using real data sets.

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Accepted/In Press date: 5 May 2017
e-pub ahead of print date: 22 June 2017
Published date: July 2017
Venue - Dates: Conference on Data and Applications Security and Privacy: 31st Annual IFIP WG 11.3, Philadelphia, United States, 2017-07-19 - 2017-07-21
Organisations: Electronics & Computer Science, Electronic & Software Systems


Local EPrints ID: 410623
PURE UUID: 4b38b6a0-59c6-4274-b517-c66635095fc2

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Date deposited: 09 Jun 2017 09:15
Last modified: 08 Aug 2017 16:31

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Author: Emre Uzun
Author: Gennaro Parlato
Author: Vijayalakshmi Atluri
Author: Anna Lisa Ferrara
Author: Jaideep Vaidya
Author: Shamik Sural
Author: David Lorenzi
Editor: G. Livraga
Editor: S. Zhu

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