Newcastle, UK March 9, 2010
Trust Economics
Aad van Moorsel
Newcastle University, UK
aad.vanmoorsel@ncl.ac.uk
outline (in randomized order)
1. trust economics methodology
2. the research parts:
• soliciting human, technical and business aspects
• models
• ontologies
• user interfaces
3. examples
• passwords and compliance budget
• digital rights management
• access management
© Aad van Moorsel, Newcastle University, 2010
2
trust economics methodology
trust economics methodology for security decisions
trade off:
legal issues,
human tendencies,
business concerns,
...
a model
of the information
system
© Aad van Moorsel, Newcastle University, 2010
stakeholders
discuss
4
trust economics research
from the trust economics methodology, the following
research follows:
1. identify human, business and technical concerns
2. develop and apply mathematical modelling
techniques
3. glue concerns, models and presentation together using
a trust economics information security ontology
4. use the models to improve the stakeholders discourse
and decisions
© Aad van Moorsel, Newcastle University, 2010
5
our involvement
1.
–
2.
–
–
3.
–
–
–
4.
–
identify human, business and technical concerns
are working on a case study in Access Management (Maciej, James, with
Geoff and Hilary from Bath)
develop and apply mathematical modelling techniques
are generalising concepts to model human behaviour, and are validating it
with data collection (Rob, Simon, with Doug, Robin and Bill from UIUC)
do a modelling case study in DRM (Wen)
glue concerns, models and presentation together using a trust economics
information security ontology
developed an information security ontology, taking into account human
behavioural aspect (Simon)
made an ontology editing tool for CISOs (John)
are working on a collaborative web-based tool (John, Simon, Stefan from
SBA, Austria)
use the models to improve the stakeholders discourse and decision
using participatory design methodology, are working with CISOs to do a user
study (Simon, Philip and Angela from UCL)
© Aad van Moorsel, Newcastle University, 2010
6
example of the trust economics methodology
passwords
Information Security Management
Find out about how users behave, what the business issues
are:
CISO1: Transport is a big deal.
Interviewer1: We’re trying to recognise this in our user classes.
CISO1: We have engineers on the road, have lots of access, and are more gifted in
IT.
Interviewer1: Do you think it would be useful to configure different user
classes?
CISO1: I think it’s covered.
Interviewer1: And different values, different possible consequences if a loss
occurs. I’m assuming you would want to be able to configure.
CISO1: Yes. Eg. customer list might or might not be very valuable.
Interviewer1: And be able to configure links with different user classes and the
assets.
CISO1: Yes, if you could, absolutely.
Interviewer1: We’re going to stick with defaults at first and allow configuration
if needed later. So, the costs of the password policy: running costs, helpdesk
staff, trade-off of helpdesk vs. productivity
CISO1: That’s right.
© Aad van Moorsel, Newcastle University, 2010
8
Information Security Management
Find out about how users behave, what the business issues
are:
Discussion of "Productivity Losses":
CISO2: But it’s proportional to amount they earn. This is productivity. eg. $1m
salary but bring $20m into the company. There are expense people and
productivity people.
Interviewer1: We have execs, “road warrior”, office drone. Drones are just a
cost.
Interviewer2: And the 3 groups have different threat scenarios.
CISO2: Risk of over-complicating it, hard to work out who is income-earner and
what proportion is income earning.
Interviewer2: But this is good point.
CISO2: Make it parameterisable, at choice of CISO.
…
CISO2: So, need to be able to drill down into productivity, cost, - esp in small
company.
© Aad van Moorsel, Newcastle University, 2010
9
a model of the IT system
10
Password Policy Composition Tool
File
Help
Breaches / Productivity / Cost
tool to communicate
the result to a CISO
[projected per annum for 100-user sample]
BREACHES
#
Full
#
Composite
#
Partial
#
Productivity
#
Costs
#
BREACHES:
Composite
Policy Properties
ss 3 350
Cla
Cla
ss 1 280
Cla
Password Change Notification:
#upper
i
upper
#upper
#
#min_length
#upper
i
#notif_days
#lower
#lower
Password Login Attempts:
Password Complexity:
i
#upper
#
#
ss 2 175
No.
ss 3 350
Cla
Organisation Properties User Properties
Password Length:
upper
#upper
#
Partial
Cla
ss 2 175
ss 1 280
Cla
Cla
ss 3 350
ss 2 175
Cla
Cla
ss 1 280
No.
No.
Full
i
#upper
char_classes
max_retries
#
lower
#
lower
Password Change Frequency:
#upper
i
#change_frequency
#lower
Generate Output
Export Policy
an information security
ontology incorporating
human-behavioural implications
Simon Parkin, Aad van Moorsel
Newcastle University, UK
Robert Coles,
Bank of America Merrill Lynch
trust economics ontology
• we want to have a set of tools that implement the trust
economics methodology
• needs to work for different case studies
• need a way to represent, maintain and interrelate relevant
information
• glue between
– problem space: technical, human, business
– models
– interfaces
© Aad van Moorsel, Newcastle University, 2010
13
Using an Ontology
• We chose to use an ontology to address these
requirements, because:
– An ontology helps to formally define concepts and
taxonomies
– An ontology serves as a means to share knowledge
• Potentially across different disciplines
– An ontology can relate fragments of knowledge
• Identify interdependencies
© Aad van Moorsel, Newcastle University, 2010
14
Business, Behaviour and Security
• Example: Password Management
– There is a need to balance security and ease-of-use
– A complex password may be hard to crack, but might
also be hard to remember
• Is there a way to:
– Identify our choices in these situations?
– Consider the potential outcomes of our choices in a
reasoned manner?
© Aad van Moorsel, Newcastle University, 2010
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Requirements
• Standards should be represented
– Information security mechanisms are guided by policies, which are increasingly
informed by standards
• The usability and security behaviours of staff must be considered
–
–
–
–
Information assets being accessed;
The vulnerabilities that users create;
The intentional or unintentional threats user actions pose, and;
The potential process controls that may be used and their identifiable effects
• CISOs must be able to relate ontology content to the security infrastructure
they manage
– Representation of human factors and external standards should be clear,
unambiguous, and illustrate interdependencies
© Aad van Moorsel, Newcastle University, 2010
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Information Security Ontology
• We created an ontology to represent the human-behavioural implications of
information security management decisions
– Makes the potential human-behavioural implications visible and comparable
• Ontology content is aligned with information security management guidelines
– We chose the ISO27002: “Code of Practice” standard
– Provides a familiar context for information security managers (e.g. CISOs, CIOs,
etc.)
– Formalised content is encoded in the Web Ontology Language (OWL)
• Human factors researchers and CISOs can contribute expertise within an
ontology framework that connects their respective domains of knowledge
– Input from industrial partners and human factors researchers helps to make the
ontology relevant and useful to prospective users
© Aad van Moorsel, Newcastle University, 2010
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Ontology - Overview
Infra.
Chapter
Proc.
1
1
hasFoundation
Behavioural
Foundation
Threat
exploitedBy
1
1
managesRiskOf
contains
*
*
Behaviour
Control
Section
1
*
*
hasRiskApproach
1
*
Guideline
Control Type
1
*
hasVulnerability
hasStakeholder
Vulnerability
*
hasSubject
contains
*
Guideline
Step
1
isMitigatedBy
contains
1
1
*
*
hasSubject
*
hasVulnerability
1
*
Asset
1
1
1
ownedBy
© Aad van Moorsel, Newcastle University, 2010
Role
18
Ontology – Password Policy Example
Chapter
Single Password Memorisation
Difficult
Number: 11
Name: “ Access Control”
hasVulnerability
Section
Number: 11.3
Name: “User Responsibilities”
Objective: ...
Password
Guideline
Number: 11.3.1
Name: “Password Use”
Control: ...
Implementation Guidance (Additional): ...
Other Information: ...
hasSubject
Implementation Guidance Step
Number: 11.3.1 (d)
Guidance: “select quality passwords with sufficient minimum length which are:
1) easy to remember;
...”
© Aad van Moorsel, Newcastle University, 2010
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Example – Password Memorisation
KEY
Classes
Vulnerability
Procedural Threat
Single Password Memorisation
Difficult
Acceptance
Capability
Maintain Password
Policy
Single Password
Forgotten
Behavioural Foundation
Infrastructure Threat
Behaviour Control
Asset
Control Type
User temporarily without access
Reduction
Make Password Easier
To Remember
Threat Consequence
Relationships
mitigated by
has vulnerability
exploited by
manages risk of
© Aad van Moorsel, Newcastle University, 2010
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Example – Recall Methods
Single Password Memorisation
Difficult
KEY
Classes
Vulnerability
Procedural Threat
Behavioural Foundation
Reduction
Educate Users in
Recall Techniques
Infrastructure Threat
Behaviour Control
Asset
Mindset
Password Stored Externally
to Avoid Recall
Insecure storage medium can
be exploited by malicious party
Control Type
Threat Consequence
Relationships
mitigated by
has vulnerability
Reduction
Implement ISO27002 Guideline 11.3.1 (b),
“avoid keeping a record of passwords”
© Aad van Moorsel, Newcastle University, 2010
exploited by
manages risk of
21
Example – Password Reset Function
Single Password Memorisation
Difficult
Transfer
Helpdesk Password
Reset Management
User temporarily without access
Capability
Reduction
Helpdesk Provided With
Identity Verification Details
Single Password
Forgotten
Password Reset Process
Laborious
Automated Password
Reset System
Temporal
Mindset
Helpdesk Busy
Employee Becomes
Impatient
User compliance diminished
Reduction
User Account
Details Stolen
Malicious party gains access
IT Helpdesk Cannot
Satisfy Reset Request
Additional Helpdesk Staff
© Aad van Moorsel, Newcastle University, 2010
User temporarily without access
22
Conclusions
• CISOs need an awareness of the humanbehavioural implications of their security
management decisions
• Human Factors researchers need a way to
contribute their expertise and align it with
concepts that are familiar to CISOs
– Standards
– IT infrastructure
– Business processes
• We provided an ontology as a solution
– Serves as a formalised base of knowledge
– one piece of the Trust Economics tools
© Aad van Moorsel, Newcastle University, 2010
23
an ontology for structured systems economics
Adam Beaument
UCL, HP Labs
David Pym
HP Labs, University of Bath
ontology to link with the models
thus far, trust economics ontology represent technology
and human behavioural issues
how to glue this to the mathematical models?
© Aad van Moorsel, Newcastle University, 2010
25
ontology
© Aad van Moorsel, Newcastle University, 2010
26
© Aad van Moorsel, Newcastle University, 2010
27
conclusion on trust economics ontology
trust economics ontology is work in progress
- added human behavioural aspects to IT security
concepts
- provided an abstraction that allows IT to be
represented tailored to process algebraic model
to do:
- complete as well as simplify...
- proof is in the pudding: someone needs to use it in a
case study
© Aad van Moorsel, Newcastle University, 2010
28
an ontology editor and a community ontology
John Mace (project student)
Simon Parkin
Aad van Moorsel
Stefan Fenz
SBA, Austria
Stakeholders
• Chief Information Security Officers (CISOs)
• Human Factors Researchers
• Ontology experts
30
Current Ontology Development
•
•
•
•
Requires use of an ontology creation tool
Graphical or text based tools
Both create machine readable ontology file from user input
User must define underlying ontology structure
31
Current Development Issues
• Knowledge required of ontology development and tools
• Development knowledge held by ontology experts and not those
whose knowledge requires capture
• Current tools are complex and largely aimed at ontology experts
• Process is time-consuming and error prone
32
how would you want to write ontology content?
<Vulnerability rdf:about="#SinglePasswordMemorisationDifficult">
<mitigatedBy rdf:resource="#MakePasswordEasierToRemember"/>
<exploitedBy rdf:resource="#SinglePasswordForgotten"/>
</Vulnerability>
33
Proposed Solution
• A simple, intuitive tool to create/modify ontology in graphical
form
• Captures knowledge of domain experts while removing need to
know of ontology construction techniques
• Underlying information security ontology structure is predefined
• Interactive help system and mechanisms to minimise error
34
Implementation Overview
Chief Information Security Officer (CISO) /
Human Factors Researcher (HFR)
enter content
load
existing
diagram
Ontology Diagram Store
ontology
diagram
save
current
diagram
Java Translation Program
Ontology Editor
35
ontology
file
Ontology File Store
Ontology Editor
36
Adding New Concept
37
Ontology Diagram
38
Java Translation Program
Ontology Diagram
diagram
saved to
Temp
folder
Ontology File
diagram
retrieved
from Temp
folder
file saved
file created
user defined
parameters
Java Translation Program
Ontology Editor
Ontology File Store
Java libraries imported
Java 1.5 API
Xerces API
OWL API
39
Ontology File
• Written in machine readable Web Ontology Language OWL
• Created using OWL API
• File structure:
– Header
– Classes
– Data properties
– Object properties
– Individuals
40
Ontology File Example
<Vulnerability rdf:about="#SinglePasswordMemorisationDifficult">
<mitigatedBy rdf:resource="#MakePasswordEasierToRemember"/>
<exploitedBy rdf:resource="#SinglePasswordForgotten"/>
</Vulnerability>
41
Summary
• Need for information security ontology editing tool
• Proposed tool allows domain experts to develop ontology without
knowledge of ontology construction
• Delivers machine readable ontology files
• Simplifies development process
• Allow further development of ‘base’ ontology
42
Future Developments
• Ontology too large for small group to develop effectively
• Vast array of knowledge held globally
• Ontology development needs to be a collaborative process to be
effective
• Web-oriented collaborative editing tool
• Basis for 3rd year dissertation
43
user evaluation for trust economics software
Simon Parkin
Aad van Moorsel
Philip Inglesant
Angela Sasse
UCL
participatory design of a trust economics tool
assume we have all pieces together:
• ontology
• models
• CISO interfaces
what should the tool look like?
we conduct a participatory design study with CISOs from:
• ISS
• UCL
• National Grid
method: get wish list from CISOs, show a mock-up tool and
collect feedback, improve, add model in background, try it
out with CISOs, etc.
© Aad van Moorsel, Newcastle University, 2010
45
Password Policy Composition Tool
File
Help
Breaches / Productivity / Cost
tool to communicate
the result to a CISO
[projected per annum for 100-user sample]
BREACHES
#
Full
#
Composite
#
Partial
#
Productivity
#
Costs
#
BREACHES:
Composite
Policy Properties
ss 3 350
Cla
Cla
ss 1 280
Cla
Password Change Notification:
#upper
i
upper
#upper
#
#min_length
#upper
i
#notif_days
#lower
#lower
Password Login Attempts:
Password Complexity:
i
#upper
#
#
ss 2 175
No.
ss 3 350
Cla
Organisation Properties User Properties
Password Length:
upper
#upper
#
Partial
Cla
ss 2 175
ss 1 280
Cla
Cla
ss 3 350
ss 2 175
Cla
Cla
ss 1 280
No.
No.
Full
i
#upper
char_classes
max_retries
#
lower
#
lower
Password Change Frequency:
#upper
i
#change_frequency
#lower
Generate Output
Export Policy
CISO user interfaces
Policy Properties
Organisation Properties User Properties
Manned Helpdesk - No. of Staff:
Manned Helpdesk - Staff Salary:
Automated Helpdesk Annual Support Cost:
Manned Helpdesk – Reset
Request Completion Time:
Automated Helpdesk – Reset
Request Completion Time:
GBP
USD
Hrs
Mins
Helpdesk Strategy:
Manned
Automated
i
Password Length
RELATED GUIDELINE(S)
Guideline: ISO27002 - 11.3.1(d)
VULNERABILITIES
Vulnerability: Password entry may be observed
Threat: Password may be guessed by someone
Vulnerability: Password entry may become impractical
Threat: Typographical errors result in login failure
Threat: Typographical errors result in account lockout
Threat: Login entry takes too long
OK
© Aad van Moorsel, Newcastle University, 2010
47
Information Security Management
Find out about how users behave, what the business issues
are:
CISO1: Transport is a big deal.
Interviewer1: We’re trying to recognise this in our user classes.
CISO1: We have engineers on the road, have lots of access, and are more gifted in
IT.
Interviewer1: Do you think it would be useful to configure different user
classes?
CISO1: I think it’s covered.
Interviewer1: And different values, different possible consequences if a loss
occurs. I’m assuming you would want to be able to configure.
CISO1: Yes. Eg. customer list might or might not be very valuable.
Interviewer1: And be able to configure links with different user classes and the
assets.
CISO1: Yes, if you could, absolutely.
Interviewer1: We’re going to stick with defaults at first and allow configuration
if needed later. So, the costs of the password policy: running costs, helpdesk
staff, trade-off of helpdesk vs. productivity
CISO1: That’s right.
© Aad van Moorsel, Newcastle University, 2010
48
Information Security Management
Find out about how users behave, what the business issues
are:
Discussion of "Productivity Losses":
CISO2: But it’s proportional to amount they earn. This is productivity. eg. $1m
salary but bring $20m into the company. There are expense people and
productivity people.
Interviewer1: We have execs, “road warrior”, office drone. Drones are just a
cost.
Interviewer2: And the 3 groups have different threat scenarios.
CISO2: Risk of over-complicating it, hard to work out who is income-earner and
what proportion is income earning.
Interviewer2: But this is good point.
CISO2: Make it parameterisable, at choice of CISO.
…
CISO2: So, need to be able to drill down into productivity, cost, - esp in small
company.
© Aad van Moorsel, Newcastle University, 2010
49
example of the trust economics methodology
access management
Maciej Machulak (also funded by JISC SMART)
James Turland (funded by EPSRC AMPS)
Wen Zeng (for DRM)
Aad van Moorsel
Geoff Duggan
Hilary Johnson
University of Bath
Project Description
• The SMART (Student-Managed Access to Online Resources)
project will develop an online data access management
system based on the User-Managed Access (UMA) Web
protocol, deploy it within Newcastle University and
evaluate the system through a user study.
– The project team will also contribute to the
standardisation effort of the UMA protocol by actively
participating in the User-Managed Access Work Group
(UMA WG – charter of the Kantara Initiative)
51
Project Description - UMA
• User-Managed Access protocol – allows an individual control
the authorization of data sharing and service access made
between online services on the individual's behalf.
Source: http://kantarainitiative.org/confluence/display/uma/UMA+Explained
52
Project Description – Objectives
• Objectives:
– Define scenario for UMA use case within Higher
Education (HE) environments
– Develop UMA-based authorisation solution
– Deploy the UMA-based solution within Newcastle
University:
• Integrate the system with institutional Web
applications
• Evaluate the system through a user study
– Contribute with the scenario, software and project
findings to the UMA WG and actively participate in the
standardisation effort of the UMA Web protocol.
– Demonstrate, document and disseminate project
outputs
53
trust economics applied to access management
• we build the application
• we build models to quantify trust or CIA properties
• we investigate user interfaces and user behaviour to
input into the model
related: we also build DRM models, trading off
productivity and confidentiality
54
modelling concepts and model validation
Rob Cain (funded by HP)
Simon Parkin
Aad van Moorsel
Doug Eskin (funded by HP)
Robin Berthier
Bill Sanders
University of Illinois at Urbana-Champaign
project objectives
• performance models traditionally have not included human
behavioural aspects in their models
• we want to have generic modelling constructs to represent
human behaviour, tendencies and choices:
– compliance budget
– risk propensity
– impact of training
– role dependent behaviour
• we want to validate our models with collected data
– offline data, such as from interviews
– online data, measure ‘live’
• we want to optimise the data collection strategy
• in some cases, it makes sense to extend our trust economics
methodology with a strategy for data
collection
56
Presentation of Mobius
57
Sample Results
Without Comp Budget Feedback
380
360
340
320
Utility
300
HB Score
280
260
240
220
0
0.1
0.2
0.3
0.4
0.5
0.6
Prob of Encryption
58
0.7
0.8
0.9
1
Sample Mobius Results (Cont.)
Using Comp Budget Feedback
380
360
340
320
Utility
300
HB Score
280
260
240
220
0
0.1
0.2
0.3
0.4
0.5
0.6
Prob of Encryption
59
0.7
0.8
0.9
1
Criticality of Using Data
• The goal of using data is to provide credibility to the
model:
– By defining and tuning input parameters according to
individual organization
– By assessing the validity of prediction results
• Issues:
– Numerous data sources
– Collection and processing phases are expensive and
time consuming
– No strategy to drive data monitoring
– Mismatch between model and data that can be
collected
60
Data Collection Approach
Stakeholders
1
2
Data
Sources
Cost / Quality
Model
Importance
3
4
1.
2.
3.
4.
•
•
Input parameter definition
Output validation
Design specialized model according to requirements
Classify potential data sources according to their cost and quality
Optimize collection of data according to parameter importance
Run data validation and execute model
61
Data Sources Classification
• Cost:
– Cost to obtain
– Time to obtain
– Transparency
– Legislative process
• Quality:
– Accuracy
– Applicability
• Importance:
– Influence of parameter value on output
62
Organization Budget Parameters
input/o
Category
utput
Parameter
Description
Variables
Influence
Data Sources and Cost
IT security survey
(http://www.gartner.com,
http://www.gocsi.com)
in
Budget
Total security
investment
IT budget. Default
is 100
medium
interview with IT directors
public gov. budget data
in
in
in
Budget
Training
investment
Training budget.
Always, one-off
100
USB stick =
100, software =
0, install and
maintenance =
0
Experimental
value. Proportion
Support proportion
of Active Security
Budget
of budget
Investment used
for support
Budget
Low
Medium
High
Monitoring
proportion of
budget
interview with IT directors
low
public gov. budget data
interview with IT directors
high
public gov. budget data
Experimental
value. 1 – (Support
proportion of
budget)
interview with IT directors
high
public gov. budget data
© Aad van Moorsel, Newcastle University,
63 2010
63
Overall Human Parameters
input/
output
in
in
Category
User
behavior
User
behavior
Parameter
Description
Compliance
budget
Effort willing to
spend
conforming
with security
policy that
doesn't benefit
you.
Perceived
benefit of task
Effort willing to
put in without
using
compliance
budget.
Variables
Influence
Generalised:
understanding,
investment,
incentives
© Aad van Moorsel, Newcastle University,
64 2010
64
Data Sources and Cost
User survey
Password: Probability of Break-in
input/ou
tput
Category
Parameter
in
Culture of
organization
in
User behavior Password strength
in
Attacker
Password strength
determination threshold
in
User behavior
Password update
frequency
in
User behavior
in
Description
Prob, of leaving default
password
Variables
Influence
Organization policy, user training
medium
Organization policy, user training
medium
Password stength, attacker
determination
medium
Organization policy, user training
medium
Prob. of being locked
out
when password is forgotten Organization policy, user training
medium
User interface
Prob. of finding lost
password
efficiency of password
recovery tech.
medium
in
User interface
Prob. of needing
support
(#support queries / #users) prob. of forgetting password
medium
in
User behavior
Management
reprimands
medium
in
User behavior
Negative support
experiences
medium
out
User behavior
Prob. password can be
compromised
out
Security
Availability
#successful data transfer
high
out
Security
Confidentiality
#exposures + #reveals
high
Compromised by brute
force attack
high
65
Data Sources and Cost
data collection research
four sub problems:
• determine which data is needed to validate the model:
– provide input parameter values
– validate output parameters
• technical implementation of the data collection
• optimize data collection such that cost is within a certain
bound: need to find the important parameters and trade
off with cost of collecting it
• add data collection to the trust economics methodology:
– a data collection strategy will be associated with the
use of a model
66
conclusion
trust economics research in Newcastle:
• ontology for human behavioural aspects, incl. editor and
community version
• tool design with CISOs
• modelling: DRM and Access Management
• data collection strategies for validation
work to be done:
• generic ontology for trust economics, underlying the tools
• actual tool building
• evaluation of the methodology
and formulate a publication strategy
© Aad van Moorsel, Newcastle University, 2010
67
trust economics info
http://www.trust-economics.org/
Publications:
• An Information Security Ontology Incorporating Human-Behavioural Implications. Simon Parkin, Aad van Moorsel,
Robert Coles. International Conference on Security of Information and Networks, 2009
• Risk Modelling of Access Control Policies with Human-Behavioural Factors. Simon Parkin and Aad van Moorsel.
International Workshop on Performability Modeling of Computer and Communication Systems, 2009.
• A Knowledge Base for Justified Information Security Decision-Making. Daria Stepanova, Simon Parkin, Aad van Moorsel.
International Conference on Software and Data Technologies, 2009.
• Architecting Dependable Access Control Systems for Multi-Domain Computing Environments. Maciej Machulak, Simon
Parkin, Aad van Moorsel. Architecting Dependable Systems VI, R. De Lemos, J. Fabre C. Gacek, F. Gadducci and M. ter
Beek (Eds.), Springer, LNCS 5835, pp. 49—75, 2009.
• Trust Economics Feasibility Study. Robert Coles, Jonathan Griffin, Hilary Johnson, Brian Monahan, Simon Parkin, David
Pym, Angela Sasse and Aad van Moorsel. Workshop on Resilience Assessment and Dependability Benchmarking, 2008.
• The Impact of Unavailability on the Effectiveness of Enterprise Information Security Technologies. Simon Parkin,
Rouaa Yassin-Kassab and Aad van Moorsel. International Service Availability Symposium, 2008.
Technical reports:
• Architecture and Protocol for User-Controlled Access Management in Web 2.0 Applications. Maciej Machulak, Aad van
Moorsel. CS-TR 1191, 2010
• Ontology Editing Tool for Information Security and Human Factors Experts. John Mace, Simon Parkin, Aad van Moorsel.
CS-TR 1172, 2009
• Use Cases for User-Centric Access Control for the Web, Maciej Machulak, Aad van Moorsel. CS-TR 1165, 2009
• A Novel Approach to Access Control for the Web. Maciej Machulak, Aad van Moorsel. CS-TR 1157, 2009
• Proceedings of the First Trust Economics Workshop. Philip Inglesant, Maciej Machulak, Simon Parkin, Aad van Moorsel,
Julian Williams (Eds.). CS-TR 1153, 2009.
• A Trust-economic Perspective on Information Security Technologies. Simon Parkin, Aad van Moorsel. CS-TR 1056, 2007
© Aad van Moorsel, Newcastle University, 2010
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