14
1.6 assurance and accountaBIlIty Framework
In general, mechanisms to build trust in cloud computing fall in to two
main categories—assurance and accountability. Standards, certification,
and communication strategies seek to assure the consumers by providing
cues of CSP competence, integrity, and benevolence, and to some extent
consistency. Regulation and contractual mechanisms seek to hold CSPs
accountable in the event of a trust violation. A key problem is that these
initiatives are currently highly fragmented, with multiple initiatives by as
many stakeholders, but no particular comprehensive, coordinated, and
holistic framework of activity that provides direction for policy makers,
users, cloud service providers, and indeed researchers.
Figure 1.1 below presents an integrated multi-stakeholder framework
for assurance and accountability for cloud-based trust building. It extends
the chain of accountability concept first proposed by Pearson and
Wainwright (2013) to provide transparency and clarity on liability in the
event of a data breach in the cloud. While Pearson and Wainwright (2013)
envisaged a set of mechanisms for mitigating risk (preventative controls),
monitoring and identifying risk and policy violations (detective controls),
and providing redress (corrective controls), their approach is largely built
on calculative trust-based model whereby accountability is both quantitative and absolute. The goal is to eliminate distrust or mitigate the negative
impact of a trust violation. In effect, it is an ab initio pre-emptive trust
repair approach.
In contrast, we propose, a more positive approach couched in theories
of trust building and repair. The focus is on trust building mechanisms;
trust repair mechanisms only initiate when a trust violation occurs. Based
on our work in Lynn et al. (2014), we suggest that cloud consumers
should have control of their data, how it is used, where it is used, and who
should use it, and this should be auditable by all involved. They should
have a say, if they want it, but as a default standard declarations should be
weighed towards the best interests of the consumer, and neither prejudicial to consumer rights, nor contrary to government policy. As such, we
propose that in addition to preventative controls, there are declarative
controls where all parties can declare their policies and expectations irrespective of contracts or policies which seek to circumvent local laws and
regulation. Furthermore, there are confirmative controls that report and
alert stakeholders that these policies and expectations are being met. In
this way, trust is not only being built on the basis on rules and transactions, but proactive mechanisms are in place so that knowledge-based
T. LYNN ET AL.
1.6 assurance and accountaBIlIty Framework
In general, mechanisms to build trust in cloud computing fall in to two
main categories—assurance and accountability. Standards, certification,
and communication strategies seek to assure the consumers by providing
cues of CSP competence, integrity, and benevolence, and to some extent
consistency. Regulation and contractual mechanisms seek to hold CSPs
accountable in the event of a trust violation. A key problem is that these
initiatives are currently highly fragmented, with multiple initiatives by as
many stakeholders, but no particular comprehensive, coordinated, and
holistic framework of activity that provides direction for policy makers,
users, cloud service providers, and indeed researchers.
Figure 1.1 below presents an integrated multi-stakeholder framework
for assurance and accountability for cloud-based trust building. It extends
the chain of accountability concept first proposed by Pearson and
Wainwright (2013) to provide transparency and clarity on liability in the
event of a data breach in the cloud. While Pearson and Wainwright (2013)
envisaged a set of mechanisms for mitigating risk (preventative controls),
monitoring and identifying risk and policy violations (detective controls),
and providing redress (corrective controls), their approach is largely built
on calculative trust-based model whereby accountability is both quantitative and absolute. The goal is to eliminate distrust or mitigate the negative
impact of a trust violation. In effect, it is an ab initio pre-emptive trust
repair approach.
In contrast, we propose, a more positive approach couched in theories
of trust building and repair. The focus is on trust building mechanisms;
trust repair mechanisms only initiate when a trust violation occurs. Based
on our work in Lynn et al. (2014), we suggest that cloud consumers
should have control of their data, how it is used, where it is used, and who
should use it, and this should be auditable by all involved. They should
have a say, if they want it, but as a default standard declarations should be
weighed towards the best interests of the consumer, and neither prejudicial to consumer rights, nor contrary to government policy. As such, we
propose that in addition to preventative controls, there are declarative
controls where all parties can declare their policies and expectations irrespective of contracts or policies which seek to circumvent local laws and
regulation. Furthermore, there are confirmative controls that report and
alert stakeholders that these policies and expectations are being met. In
this way, trust is not only being built on the basis on rules and transactions, but proactive mechanisms are in place so that knowledge-based
T. LYNN ET AL.