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Towards adaptive access control

Towards adaptive access control
Towards adaptive access control
Access control systems are nowadays the first line of defence of modern
IT systems. However, their effectiveness is often compromised by policy
miscofigurations that can be exploited by insider threats. In this paper, we present
an approach based on machine learning to refine attribute-based access control
policies in order to reduce the risks of users abusing their privileges. Our approach
exploits behavioral patterns representing how users typically access resources
to narrow the permissions granted to users when anomalous behaviors are detected.
The proposed solution has been implemented and its effectiveness has been
experimentally evaluated using a synthetic dataset.
1-10
Argento, Luciano
f544a605-0130-47ce-819c-eb6ff7e3c7c2
Margheri, Andrea
4b87c32d-3eaf-445e-8ac0-8207daace2e1
Paci, Federica
9fbf3e5b-ae03-40e8-a75a-3657cbc9216e
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7
Zannone, Nicola
c92b7e50-a300-4681-a7f4-f4741dcc7c62
Argento, Luciano
f544a605-0130-47ce-819c-eb6ff7e3c7c2
Margheri, Andrea
4b87c32d-3eaf-445e-8ac0-8207daace2e1
Paci, Federica
9fbf3e5b-ae03-40e8-a75a-3657cbc9216e
Sassone, Vladimiro
df7d3c83-2aa0-4571-be94-9473b07b03e7
Zannone, Nicola
c92b7e50-a300-4681-a7f4-f4741dcc7c62

Argento, Luciano, Margheri, Andrea, Paci, Federica, Sassone, Vladimiro and Zannone, Nicola (2018) Towards adaptive access control. At 32nd Annual IFIP WG 11.3<br/>Conference on Data and Applications Security and Privacy (16/07/18) 32nd Annual IFIP WG 11.3<br/>Conference on Data and Applications Security and Privacy. 10 pp, pp. 1-10.

Record type: Conference or Workshop Item (Paper)

Abstract

Access control systems are nowadays the first line of defence of modern
IT systems. However, their effectiveness is often compromised by policy
miscofigurations that can be exploited by insider threats. In this paper, we present
an approach based on machine learning to refine attribute-based access control
policies in order to reduce the risks of users abusing their privileges. Our approach
exploits behavioral patterns representing how users typically access resources
to narrow the permissions granted to users when anomalous behaviors are detected.
The proposed solution has been implemented and its effectiveness has been
experimentally evaluated using a synthetic dataset.

Text AdaptiveAccessControl - Accepted Manuscript
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More information

Published date: 2018
Venue - Dates: 32nd Annual IFIP WG 11.3<br/>Conference on Data and Applications Security and Privacy, 2018-07-16

Identifiers

Local EPrints ID: 421536
URI: https://eprints.soton.ac.uk/id/eprint/421536
PURE UUID: 7c30e2bb-b468-4fbe-8b5f-c831e62039b3
ORCID for Andrea Margheri: ORCID iD orcid.org/0000-0002-5048-8070

Catalogue record

Date deposited: 14 Jun 2018 16:30
Last modified: 06 Oct 2018 00:30

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