Analyzing Quality Criteria in Role-based Identity and Access

Management

Michael Kunz

, Ludwig Fuchs

1,2

, Michael Netter

1,2

and G

unther Pernul

University of Regensburg, Regensburg, Germany

Nexis GmbH, M

unster, Germany

Keywords:

Role Quality, Role Mining, RBAC, Identity and Access Management.

Abstract:

Roles have turned into the de facto standard for access control in enterprise identity management systems.

However, as roles evolve over time, companies struggle to develop and maintain a consistent role model.

Up to now, the core challenge of measuring the current quality of a role model and selecting criteria for its

optimization remains unsolved. In this paper, we conduct a survey of existing role mining techniques and

identify quality criteria inherently used by these approaches. This guides organizations during the selection of

a role mining technique that matches their company-speciﬁc quality preferences. Moreover, our analysis aims

to stimulate the research community to integrate quality metrics in future role mining approaches.

1 INTRODUCTION

Regulating access to resources is an elementary func-

tion of every identity management system (IdMS).

Not just as a result of governmental regulations or

compliance requirements like the Sarbanes-Oxley Act

((SOX, 2002)), Basel III ((Basel Comittee on Banking

Supervisions, 2010)), or the EU General Data Protec-

tion Regulation ((European Union, 2012)) in its re-

vised form, especially medium- and large-sized com-

panies are forced to control access to sensitive infor-

mation. Over the past decades, Role-Based Access

Control (RBAC, (Sandhu et al., 1996)), has become

the de facto standard for managing access to resources

in IT systems. In RBAC, roles act as intermediary be-

tween users and permissions. Despite being widely

used, RBAC struggles with the dynamic evolution of

role models over time. Besides the daily user ad-

ministration, the central challenge after setting up a

role model is its strategic maintenance. Role system

maintenance focuses on updating and cleansing role

conﬁgurations, discarding unused, and deﬁning new

roles. Changing business processes, organizational

structures, or security policies and newly imposed

regulations force administrators to quickly adapt the

access control structures in place. Commonly, this

leads to an increasing role number, an overall reduc-

tion of the role model quality and the advent of se-

curity vulnerabilities due to wrongly assigned or out-

dated role deﬁnitions.

In order to mitigate the risk of increasing security

vulnerabilities in RBAC, one cornerstone of ensuring

a high role model quality is the periodic assessment

of the role model components, such as the user-role

assignments (UA), the role-permission assignments

(RA), or role hierarchy structures. Role mining ap-

proaches that support organizations during their ini-

tial setup of an RBAC model have attracted the at-

tention of researchers. Over the last four years, for

instance, a variety of research groups have published

approaches to generate an initial set of roles. However

hardly any attention has been drawn to the mainte-

nance of existing role models. Recently, the need for

investigating and cleaning role model structures has

been highlighted by (Fuchs et al., 2014). However,

the core challenge of measuring the current quality of

a role model and selecting criteria for its optimization

still remains unsolved. Due to its importance for ac-

cess control it is likely that role mining is re-applied

periodically by organizations in order to ensure role

model correctness. Our work builds on both, the in-

depth investigation of the research area as well as

our practical experience from industry projects within

medium- and large-sized companies dealing with the

setup and management of a role-based IdMS. Simi-

lar to (Fuchs et al., 2014), we argue that the practical

project requirements cannot be considered to a sufﬁ-

cient extent by the available role mining approaches.

In particular, we address the following research ques-

tion (RQ): Which quality criteria are employed in ex-

Kunz M., Fuchs L., Netter M. and Pernul G..

Analyzing Quality Criteria in Role-based Identity and Access Management.

DOI: 10.5220/0005232100640072

In Proceedings of the 1st International Conference on Information Systems Security and Privacy (ICISSP-2015), pages 64-72

ISBN: 978-989-758-081-9

 2015 SCITEPRESS (Science and Technology Publications, Lda.)

Use of quality criteria in existing

Role Mining approaches

Literature

Survey

Classification &

Criteria elicitation

Role

Mining

catalogue

Figure 1: Research methodology.

isting role mining approaches?

Hence, the contribution of this work is twofold.

In order to close the existing research gap, this paper

ﬁrstly analyzes the development of role mining, pre-

senting a survey of the ﬁeld and underlining the rapid

development in the area. In this respect, it builds on

an existing survey of the area published in the year

2011. During execution, various role mining algo-

rithms rely on some sort of quality criteria to differ-

ent extents. As a result, this paper secondly extracts

potential criteria for rating the quality of role models

included in current role mining approaches. It points

out the differences among the approaches and under-

lines the need for a structured quality rating process.

We thereby aim at stimulating the research commu-

nity and encourage them to enrich existing role min-

ing approaches considering quality criteria in a struc-

tured manner.

2 RELATED WORK

In todays medium- and large-sized companies, Role-

based Access Control has become the de facto stan-

dard for controlling user access to resources. As a

result of the large amount of research output, sev-

eral surveys of the general area of roles in IT secu-

rity have been presented (e.g. (Zhu and Zhou, 2008)

and (Fuchs et al., 2011)). Authors lately agreed upon

the growing importance of role development in gen-

eral and automated role mining in speciﬁc. Fuchs et

al., for instance, provided an evaluation of role de-

velopment approaches in (Fuchs and M

uller, 2009)

and (Fuchs and Meier, 2011). Since their publication,

the research output in the area has grown more than

double, requiring a survey update in order to give an

in-depth understanding of recent developments.

During the initial setup of a role model, role min-

ing algorithms inherently rely on different quality cri-

teria to various extents. Nevertheless, no structured

analysis considering those criteria has been executed

so far. It has rather been shown that popular role

mining approaches like (Molloy et al., 2010), (Giblin

et al., 2010), or (Takabi and Joshi, 2010) do not offer

the guidance required to judge the correctness of role

deﬁnitions and role models (Fuchs et al., 2014). In

practice, however, it is very likely that companies re-

apply role mining techniques in order to ensure role

model correctness after having employed a role min-

ing approach for the initial role setup. Yet, none of

the related work in the ﬁeld focuses on quality criteria

applied during role system maintenance. In (Molloy

et al., 2008), the authors investigated the usage of se-

lected metrics like the Weighted Structural Complex-

ity (WSC) for analyzing role system states. (Fuchs

and M

uller, 2009) described mechanisms for periodi-

cally evaluating a role systems quality but do not con-

sider the scalability of their approach in large real-

world scenarios. (Fuchs et al., 2014) recently pro-

posed the integration of a distinct quality rating and

role classiﬁcation phase in their role optimization pro-

cess model. However, they do not present an overview

of available quality criteria and their application. As

a result, the core challenge of measuring the current

quality of a role model still remains unsolved.

3 METHODOLOGY

Our methodology to answer the research questions

presented in Section 1 is depicted in Figure 1. At

ﬁrst, we survey the research area and create a catalog

of role mining approaches that serves as the basis for

further analyses (step 1). For this literature survey, we

follow the methodology proposed by (Levy and Ellis,

2006). We carried out a bibliographic database search

including the ACM Digital Library, DBLP, IEEE Dig-

ital Library, and Google Scholar using the keyword

”role mining”. To arrive at a complete catalog of role

mining approaches, author and reference search for

each publication was applied to identify previously

undiscovered research. Finally, papers that do not

present role mining techniques were removed from

the catalog (e.g. (Molloy et al., 2008)). Consecu-

tively, we classify recent role mining publications ac-

cording to the scheme presented by (Fuchs and Meier,

2011). Additional clusters were added for role min-

ing approaches that used new techniques. Note, that

approaches that rely on more than one role mining

technique were clustered based on the predominant

technique being used. At this stage we completed our

ﬁrst contribution by extending the existing survey and

highlighting the rapid increase of research within the

last three years as well as the further diversiﬁcation

of role mining techniques used. During step 2 of our

methodology we answer RQ by investigating the us-

age of quality criteria in role mining algorithms.

4 ROLE MINING SURVEY

This section extends a survey on role mining research

conducted by (Fuchs and Meier, 2011). Figure 2 un-

AnalyzingQualityCriteriainRole-basedIdentityandAccessManagement

1 1

13 13

21 21

Number of Publications

Year of Publication

Figure 2: Development of the research area.

derlines the importance of an updated interpretation

of role detection approaches due to the increase in re-

searchers’ attention during the last three years. Be-

tween 2011 and 2013, 55 papers related to role mining

have been published, representing an increase of 141

percent compared to the number of publications from

2003 - 2010 (39). While role mining in general con-

sists of a pre-processing phase, a role detection phase,

and a post-processing phase (Fuchs and Meier, 2011),

the remainder of this survey focuses on the role detec-

tion phase as the core element of every role mining al-

gorithm. During this phase, suitable roles are created

based on an existing set of user-permission assign-

ments (UPA). The algorithms can be grouped accord-

ing to the underlying technique. While the ﬁrst six

techniques have been previously introduced in (Fuchs

and Meier, 2011), we identiﬁed three additional tech-

niques (Visual Role Mining, Boolean Matrix Decom-

position, and Attribute-based Role Mining) being ap-

plied to solve the role mining problem for the ﬁrst

time. Additionally to the 21 algorithms published in

(Fuchs and Meier, 2011), 26 out of the 55 approaches

from 2011 to 2013 have been categorized, while the

rest is related to either pre- or post-processing phase.

Subsequently, each technique and representative pub-

lications are presented:

Subset Enumeration aims to discover roles

through creating all possible intersections of permis-

sion sets. Due to the exponential complexity of enu-

merating all possible subsets, algorithms such as (Xu

and Stoller, 2013b) use heuristics for role candidate

selection. Hence, role mining algorithms based on

this technique strive to balance complexity and qual-

ity of results. With 13 available algorithms, this is the

most frequently used technique in role mining.

Clustering is a role mining approach that is di-

rectly derived from data mining (Frank et al., 2012).

Using a UPA-matrix as input, this technique searches

for clusters with similar permissions. However, clus-

tering approaches struggle with limitations such as re-

quiring users or permissions to be only part of one

single cluster (Frank et al., 2012). To solve these

challenges, several clustering variants exist. Exam-

ples include iterative application of the technique or

reduction of the input (Lu et al., 2013; Huang et al.,

2012).

Graph Optimization uses bipartite graphs to rep-

resent the UPA (Colantonio et al., 2009). As roles rep-

resent an intermediary between the two disjoint ver-

tices of users and permissions, those approaches aim

at converting the bipartite into a tripartite graph or a

representation with sub-graphs. Roles are then repre-

sented by the middle vertex (Colantonio et al., 2009)

or each necessary sub-graph (Mandala et al., 2012).

Frequent Permission Set Mining has its roots in

marketing analysis and algorithms of generic frequent

set mining (Agrawal et al., 1993). Initially used for

the study of consumers’ purchase behavior, it is ap-

plied by role mining algorithms in order to discover

permissions that frequently occur together. The pre-

sumption is that permission sets that appear together

can be interpreted as role candidates.

Formal Concept Analysis is a data mining tech-

nique similar to clustering, overcoming the limitation

of only assigning entities to one group (Molloy et al.,

2008). Related algorithms build a concept lattice from

the UPA-matrix and reduce duplicate information. A

concept lattice is a construct similar to a graph and

represents roles and their connection in a partially

ordered collection of clusters which again consist of

permissions and users.

Heuristic Matrix Selection is similar to Subset

Enumeration without the initial role set being based

on intersections of permissions. Instead, it iterates

through rows (or columns) and picks role candidates

successively according to the highest number of given

assignments (e.g permissions assigned to a user). Ini-

tially, each row/column is treated as a role. Subse-

quently, a cross-check for duplicate roles is conducted

(Blundo and Cimato, 2010).

Visual Role Mining is a fairly new technique ini-

tially proposed in (Colantonio et al., 2012). It re-

orders rows and columns of the input UPA-matrix in

order to create clusters of adjoined permissions. Dis-

played to an administrator, the underlying assump-

tion is that humans’ cognitive capabilities and context

knowledge are better suited to discover proper roles

compared to purely algorithm-based approaches.

Boolean Matrix Decomposition is an approach

that directly addresses the Role Mining Problem

(RMP) introduced by (Vaidya et al., 2007). This for-

mal deﬁnition of role mining and targets at decom-

posing the boolean UPA-matrix into two separate ma-

trices, a UA-matrix and a PA-matrix. By dividing the

initial UPA-matrix into two consistent sub-matrices,

the columns of the UA-matrix and the rows of the PA-

matrix build up the set of roles.

ICISSP2015-1stInternationalConferenceonInformationSystemsSecurityandPrivacy

Attribute-based Role Mining such as (Frank

et al., 2009) are trying to incorporate business in-

formation through attributes into role mining. They

rely on the assumption that additional semantic data

is available and can be taken into account. Attribute-

based approaches combine other techniques and en-

rich them with attribute-based mechanisms to arrive

at an improved role set.

5 QUALITY-RELATED CRITERIA

After their classiﬁcation we examined role mining al-

gorithms regarding their decision making processes

of including certain role candidates in their ﬁnal out-

put. We argue that this central decision making pro-

vides well-suited indicators for quality management

in RBAC. This assumption is based on the claims

of several publications (e.g. (Xu and Stoller, 2012),

(Zhang et al., 2013b)) of outperforming competitive

approaches in terms of the quality of generated roles.

A total of 23 different quality criteria can be identi-

ﬁed. They either focus on the quality of the overall

RBAC state, the quality of single roles, or both. At

ﬁrst we focus on RBAC state quality criteria. Sec-

ondly, we examine criteria that deal with the quality

of an individual role (cf. Table 1). Note that for some

criteria (e.g. Exclude Unused Permissions) additional

input information is required. In the following, we

present a detailed interpretation of the quality criteria

and group them according to their focus.

Achieve Completeness. Completeness refers to the

exact representation of the original access control

state, i.e. the goal is to cover the initial U PA-matrix

with the resulting set of roles. In contrast to most

approaches (e.g. (Zhang et al., 2007; Vaidya et al.,

2006; Blundo and Cimato, 2010)), some techniques

allow to deviate to a certain extent from the initial

UPA-matrix based on a given threshold (the so called

δ − RMP (Vaidya et al., 2007))(Chu et al., 2012; Lu

et al., 2008). Completeness therefore measures the

quality of a RBAC state by measuring the degree to

which a resulting role set represents the initial access

control situation.

Reduce Number of Roles. Initially formulated in

the RMP, the goal of having as few roles as possible is

based on the assumption that complexity of RBAC is

directly connected to the number of roles maintained.

Thus, the number of roles in a given RBAC state is a

quality criteria usable to rate the estimated adminis-

trative efforts to manage the role model. Depending

on the size of a company in terms of its employees,

permissions and UPA, this measure can be normal-

ized in order to allow for a comparison of role models

in different organizations.

Decrease Role Set Similarity. Quality criteria re-

lated to Role Set Similarity measure the distance be-

tween two given sets of roles. They are mainly used

for the measurement of the dissimilarity of RBAC

states (e.g. in (Zhang et al., 2013a)) or the difference

between a current RBAC state and a targeted state. In

(Jafari et al., 2009), for instance, the permission simi-

larity is measured using the Euclidean Distance. Fur-

thermore, the Jaccard Similarity is a popular metric

used in a variety of approaches (Mandala et al., 2012;

Xu and Stoller, 2013a; Chu et al., 2012).

Minimize Users/Permissions per Role & Min-

imize/Maximize Roles per User/Permission.

Quality criteria assigned to this category target at

two main objectives. First, the deﬁnition of an upper

bound per role limiting the amount of users assigned

to one role. Second, the objective of ﬁnding as few

as possible permissions that are placed in a role. This

can, for instance, be applied in case an organization

aims at deﬁning a larger number of small roles

for employees that exactly ﬁt their specialist tasks.

On the contrary, maximizing the number of users or

permissions per role can be beneﬁcial other scenarios,

e.g. when organizations aim at deﬁning a small set of

large roles. Moreover, Minimizing/Maximizing the

roles per element (user or permission) is applied in

seven existing role mining approaches (e.g. see (Lu

et al., 2013; Ma et al., 2013)). This can be useful in

order to minimize the role model complexity in terms

of relationships among the role model elements.

Fullﬁll Role Constraints. Role Constraints impose

restrictions on the deﬁnition of roles. For instance,

(Ma et al., 2012) consider Segregation of Duty (SOD)

policies that entail mutually exclusive permissions in

the RBAC state. Other policies, such as the four-eye-

principle, that affect the user assignments of a role are

also conceivable.

Reduce WSC. In contrast to most other quality cri-

teria the so called Weighted Structural Complexity

(WSC) is a widely-used heuristic to rate the complex-

ity of a RBAC model. Originally introduced by (Mol-

loy et al., 2008), it applies weights to different opti-

mization objectives. It can be seen as one of the most

advanced measures that solely relies on the compo-

nents of an RBAC state. It is usable for both, indi-

vidual roles and role sets, and thus allows for a good

AnalyzingQualityCriteriainRole-basedIdentityandAccessManagement

Table 1: Quality Criteria in existing approaches.

Quality criteria State Individual Role State + Individual Role

Technique / Focus Paper

Achieve Completeness

Reduce Number of Roles g

Decrease Role Set Similarity

Minimize Users per Role

Maximize Users per Role

Minimize Roles per User

Minimize Roles per Permission

Minimize Permissions per Role

Maximize Permissions per Role

Fulﬁll Role Constraints

Reduce WSC

Optimize Matrix Sorting

Decrease Permission Similarity

Reduce Role Redundancy

Increase User Similarity

Decrease Permission Attr. Sim.

Increase Role Coverage

Exclude Unused Permissions

Consider Timestamp

Consider Role Attributes

Consider User Attributes

Group by Attributes

Subset Enumeration

(Chu et al., 2012)

(Colantonio et al., 2008a)

(Huang et al., 2012)

(Lu et al., 2013)

(Mitra et al., 2013)

(Molloy et al., 2012)

(Vaidya et al., 2006)

(Vaidya et al., 2007)

(Vaidya et al., 2010b)

(Vaidya et al., 2010a)

(Xu and Stoller, 2012)

(Xu and Stoller, 2013b)

(Zhang et al., 2013a)

Clustering

(Frank et al., 2008)

(Frank et al., 2012)

(Frank et al., 2013)

(Kumar et al., 2011)

(Schlegelmilch and Steffens, 2005)

Graph Optimization

(Colantonio et al., 2009)

(Colantonio et al., 2010)

(Ene et al., 2008)

(Gal-Oz et al., 2011)

(Hingankar and Sural, 2011)

(Mandala et al., 2012)

(Zhang et al., 2007)

Frequent Permission Set Mining

(Colantonio et al., 2008b)

(Jafari et al., 2009)

(Ma et al., 2010)

(Ma et al., 2012)

(Ma et al., 2013)

(Zhang et al., 2008)

Formal Concept Analysis

(Molloy et al., 2008)

(Wang et al., 2012)

(Wong et al., 2012)

Heuristic Matrix Selection

(Blundo and Cimato, 2010)

(Blundo and Cimato, 2013)

(Huang et al., 2010)

Visual Role Mining

(Colantonio et al., 2012)

(Eucharista, 2013)

Boolean Matrix Decomposition

(John et al., 2012)

(Lu et al., 2012)

(Lu et al., 2008)

(Uzun et al., 2011)

(Ye et al., 2013)

Attribute-based Approaches

(Frank et al., 2009)

(Han et al., 2012)

(Li et al., 2012)

Quality Criteria State Individual Role State + Individual Role

Technique / Focus Paper

Achieve Completeness

Reduce Number of Roles g

Decrease Role Set Similarity

Minimize Users per Role

Maximize Users per Role

Minimize Roles per User

Minimize Roles per Permission

Minimize Permissions per Role

Maximize Permissions per Role

Fulﬁll Role Constraints

Reduce WSC

Optimize Matrix Sorting

Decrease Permission Similarity

Reduce Role Redundancy

Increase User Similarity

Decrease Permission Attr. Sim.

Increase Role Coverage

Exclude Unused Permissions

Consider Timestamp

Consider Role Attributes

Consider User Attributes

Group by Attributes

Subset Enumeration

(Chu et al., 2012)

(Colantonio et al., 2008a)

(Huang et al., 2012)

(Lu et al., 2013)

(Mitra et al., 2013)

(Molloy et al., 2012)

(Vaidya et al., 2006)

(Vaidya et al., 2007)

(Vaidya et al., 2010b)

(Vaidya et al., 2010a)

(Xu and Stoller, 2012)

(Xu and Stoller, 2013b)

(Zhang et al., 2013a)

Clustering

(Frank et al., 2008)

(Frank et al., 2012)

(Frank et al., 2013)

(Kumar et al., 2011)

(Schlegelmilch and Steffens, 2005)

Graph Optimization

(Colantonio et al., 2009)

(Colantonio et al., 2010)

(Ene et al., 2008)

(Gal-Oz et al., 2011)

(Hingankar and Sural, 2011)

(Mandala et al., 2012)

(Zhang et al., 2007)

Frequent Permission Set Mining

(Colantonio et al., 2008b)

(Jafari et al., 2009)

(Ma et al., 2010)

(Ma et al., 2012)

(Ma et al., 2013)

(Zhang et al., 2008)

Formal Concept Analysis

(Molloy et al., 2008)

(Wang et al., 2012)

(Wong et al., 2012)

Heuristic Matrix Selection

(Blundo and Cimato, 2010)

(Blundo and Cimato, 2013)

(Huang et al., 2010)

Visual Role Mining

(Colantonio et al., 2012)

(Eucharista, 2013)

Boolean Matrix Decomposition

(John et al., 2012)

(Lu et al., 2012)

(Lu et al., 2008)

(Uzun et al., 2011)

(Ye et al., 2013)

Attribute-based Approaches

(Frank et al., 2009)

(Han et al., 2012)

(Li et al., 2012)

Uses criteria: Yes No

comparability of RBAC states. As a result of its pop-

ularity, several existing role mining approaches are

able to consider the WSC.

Optimize Matrix Sorting. Matrix sorting aims at

covering an initial access control state by sorting the

input UPA-matrix based on user accounts with sim-

ilar permissions and permissions that are assigned

a similar set of user accounts. (Colantonio et al.,

2012) introduced the ADVISER and EXTRACT al-

gorithms that generate a matrix representation of the

initial UPA-matrix that clusters permissions and user

accounts together. As a result, large areas covering

initial UPA can be visually detected by a human role

engineer.

Similarities & Redundancy. Well-known similar-

ity metrics can be applied to the various elements of

a RBAC state in order to measure its quality. (Takabi

and Joshi, 2010) gives an overview of possible appli-

cations of the Jaccard Similarity in the context of role

management. He discusses three similarity metrics

that can be applied on the assignment types of a role

(user, permission and role hierarchy). They can fur-

ther be used to compute the similarity of two role sets

(cf. Decrease Role Set Similarity). Besides examin-

ing the similarity of assignment types of a role, simi-

larity metrics are applied to attributes of role compo-

ICISSP2015-1stInternationalConferenceonInformationSystemsSecurityandPrivacy

nents. They can, for instance, be used to create a role

set based on the location attribute of all user accounts.

Distance measures are applied to identify redundant

roles (Chu et al., 2012).

Increase Role Coverage. The Role Coverage is

formally deﬁned in (Zhang et al., 2008) as the frac-

tion of role-covered UPA by the initial U PA. Compa-

nies aim at achieving a high role coverage in order to

foster the beneﬁts of RBAC compared to other access

control models. The implication of reducing admin-

istrative costs through RBAC is represented through

this criterion.

Attribute-related Criteria. Attribute-related crite-

ria evaluate the quality of a role based on its attributes

or attributes of its components. Permission usage de-

rived from access logs, for example, can be used to

display the actual usage of privileges by employees.

It offer insights into unused PA that can potentially be

removed during the next reﬁnement of a role (Molloy

et al., 2012). Furthermore, restrictions on the compo-

sition of a role, e.g. by allowing only certain attributes

of users in a role are possible (Xu and Stoller, 2012).

6 DISCUSSION

This work is motivated by the gap between the re-

cent uprising of role mining and the practical need for

periodic quality assessment of the resulting role mod-

els. The presented survey underlined the signiﬁcant

growth (141%) of published papers in the recent past.

We have shown that every role mining approach re-

lies on one or more quality criteria, mostly implicitly

without providing a structured integration of quality

management. In the following we present a short dis-

cussion of our quality-related ﬁndings from Table 1.

Firstly, it can be seen that the main quality crite-

rion in role mining is to arrive at an exact representa-

tion of existing access control states. This criterion is

– to a varying extent – considered by all available ap-

proaches, except for (Jafari et al., 2009) which derive

the roles solely from access history logs. Secondly,

Table 1 shows that a large number of approaches fo-

cus on generating as few roles as possible (Reduce

Number of Roles). Interestingly, as the WSC is a

potential criterion which is able to represent this and

other measures (by modifying its weight factors), re-

cent approaches try to use this metric as a heuristic for

producing high quality roles (Xu and Stoller, 2013b;

Eucharista, 2013; Ye et al., 2013). This can be inter-

preted as an indicator that research is already trying

to integrate sophisticated measures into role mining.

Other interesting results are, that criteria with

practical relevance up to now are only considered by

few existing approaches. Timestamps as an attribute

of permissions are, for instance, only considered by

one approach (Mitra et al., 2013). However, their in-

tegration into role mining seems promising as they

heavily can inﬂuence role design. Sets of permis-

sions activated together within a certain period of time

can e.g. represent good candidate permissions for a

role. We furthermore noted that several quality crite-

ria well-known in practice have not yet been included

in any role mining approach at all. This includes cri-

teria like the maximum allowed number of roles in

a role model, role usage or hierarchy restrictions. It

seems straightforward to integrate a maximum thresh-

old of roles to be found through automatic role dis-

covery in order to ensure the maintainability of the

whole role set. Intuitively, result sets can always be

limited by just taking the desired number of roles af-

ter sorting them according to a predeﬁned criterion.

Furthermore, the usage of UA over a certain period

of time (i.e. the activation of roles) can hint at out-

dated role deﬁnitions. Several approaches are able to

take existing roles into consideration (e.g. (Molloy

et al., 2008)) but do not integrate usage data. More-

over, restrictions on the hierarchy of a RBAC state can

represent one way to reduce complexity and increase

the quality of either a single role or the whole RBAC

state. In practice, deployed RBAC states feature un-

limited depth, sometimes even resulting in hierarchy

loops. Limiting the maximum allowed number of par-

ent or child roles of a role or the maximal hierarchy

depth can ease administrative staff’s understanding of

the overall role model. Several post-processing ap-

proaches already outline the need for an inspection of

the role hierarchy (e.g. (Guo et al., 2008; Takabi and

Joshi, 2010)). Yet, they focus on removing duplicate

hierarchy depiction and ﬁnding minimal hierarchical

assignments, not on cardinality restrictions.

7 CONCLUSION

Role-Based Access Control as the de facto standard

for managing access privileges in organizations strug-

gles with the dynamic evolution of role models over

time. As a result the quality of RBAC states initially

modeled using role mining techniques decreases over

time. In order to address this challenge, role mining

mechanisms applied during role system maintenance

need to be extended in order to integrate a dedicated

quality management stage for rating and improving

a role system state on the basis of company-speciﬁc

quality criteria. In this paper we presented two con-

AnalyzingQualityCriteriainRole-basedIdentityandAccessManagement

tributions in that respect. We ﬁrstly provided a survey

giving an overview of current role mining approaches.

The signiﬁcant increase of research activity and the

growing number of applied techniques for generating

roles during the last three years underlines the rele-

vance and diversiﬁcation of the area. By extracting

criteria that are dedicated to improving role quality

from currently available role mining approaches we

were able to answer the research question stated in

Section 1. We have shown on which quality crite-

ria current role mining approaches rely and revealed

a number of practically relevant but yet untreated cri-

teria in research. The integration of quality mecha-

nisms in order to allow for an improved selection of

role mining approaches in a given scenario based on

company-speciﬁc quality criteria.

ACKNOWLEDGEMENTS

The research leading to these results was supported

by the “Bavarian State Ministry of Education, Sci-

ence and the Arts” as part of the FORSEC research

association. This work would not have been possible

without our student Christian Wawarta.

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