Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Alberto Ocello

dblp:50/2409 · DBLP profile ↗
← Back
9ranked-venue papers
0as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Security and privacy · 7Artificial intelligence and machine learning · 1Databases, data management, data science and information retrieval · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Network and information security
1 paper
Authentication and access control · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Visualization and visual analytics
visual analytics
0.112012
Visual Role Mining: A Picture Is Worth a Thousand Roles · IEEE Trans. Knowl. Data Eng. 2012
Authentication and access control
access control
0.112012
Visual Role Mining: A Picture Is Worth a Thousand Roles · IEEE Trans. Knowl. Data Eng. 2012
Authentication and access control › access control
role-based access control
0.112012
Visual Role Mining: A Picture Is Worth a Thousand Roles · IEEE Trans. Knowl. Data Eng. 2012
Authentication and access control › access control › role-based access control
role engineering
0.112012
Visual Role Mining: A Picture Is Worth a Thousand Roles · IEEE Trans. Knowl. Data Eng. 2012

Methods — techniques the papers use, named apart from their topics

probabilistic algorithm · 0.3heuristic · 0.3EXTRACT · 0.3ADVISER · 0.3
YearPublicationVenuePosition
2012 Visual Role Mining: A Picture Is Worth a Thousand Roles
abstract
This paper offers a new role engineering approach to Role-Based Access Control (RBAC), referred to as visual role mining. The key idea is to graphically represent user-permission assignments to enable quick analysis and elicitation of meaningful roles. First, we formally define the problem by introducing a metric for the quality of the visualization. Then, we prove that finding the best representation according to the defined metric is a NP-hard problem. In turn, we propose two algorithms: ADVISER and EXTRACT. The former is a heuristic used to best represent the user-permission assignments of a given set of roles. The latter is a fast probabilistic algorithm that, when used in conjunction with ADVISER, allows for a visual elicitation of roles even in absence of predefined roles. Besides being rooted in sound theory, our proposal is supported by extensive simulations run over real data. Results confirm the quality of the proposal and demonstrate its viability in supporting role engineering decisions.
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
IEEE Trans. Knowl. Data Eng.3
2011 A new role mining framework to elicit business roles and to mitigate enterprise risk
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
Decis. Support Syst.3
2010 Evaluating the Risk of Adopting RBAC Roles
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
DBSec3
2010 Mining Business-Relevant RBAC States through Decomposition
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
SEC3
2010 Taming role mining complexity in RBAC
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
Comput. Secur.3
2009 A formal framework to elicit roles with business meaning in RBAC systems
abstract
The role-based access control (RBAC) model has proven to be cost effective to reduce the complexity and costs of ac-cess permission management. To maximize the advantages offered by RBAC, the role engineering discipline has been introduced. A viable approach is to explore current applica-tions and systems to find de facto roles embedded in existing user permissions, leading to what is usually referred to as role mining. However, a key problem that has not yet been adequately addressed by existing role mining approaches is how to propose roles that have business meaning. In order to do this, we provide a new formal framework that also enjoys practical relevance. In particular, the proposed framework leverages business information—such as business processes and organization structure—to implement role mining algo-rithms. Our key observation is that a role is likely to be meaningful from a business perspective when it involves ac-tivities within the same business process or organizational units within the same branch. To measure the “spreading” of a role among business processes or organization structure, we resort to centrality indices. Such indices are used in our cost-driven approach during the role mining process. Fi-nally, we illustrate the application of the framework through a few examples.
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
SACMAT3
2009 Mining Stable Roles in RBAC
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
SEC3
2009 A Probabilistic Bound on the Basic Role Mining Problem and Its Applications
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello, Nino Vincenzo Verde
SEC3
2008 Leveraging Lattices to Improve Role Mining
Alessandro Colantonio, Roberto Di Pietro, Alberto Ocello
SEC3