The financial ROI of Cloud security and compliance is judged by decision makers in end-user organizations by the same measures as is done for Cloud computing in general, i.e. by how much it cuts up-front capital expenditure and in-house manual maintenance cost.
However, manually translating security policy into technical implementation is difficult, expensive, and error-prone (esp. for the application layer). In order to reduce security related manual maintenance cost at the end-user organization, security tools need to become more automated.
With the emergence of Cloud PaaS, it is therefore logical to move all or parts of the model-driven security architecture into the Cloud to protect and audit Cloud applications and mashups with maximal automation. In particular, policies are provided as a Cloud service to application development and deployment tools (i.e. “Policy as a Service”), and policy automation is embedded into Cloud application deployment and runtime platforms (i.e. automated policy generation/update, enforcement, monitoring).
Different Cloud deployment scenarios are possible, which differ from local non-Cloud deployments where model-driven security is conventionally installed within or alongside a locally installed development tool (e.g. Eclipse). Policy as a Service (see ObjectSecurity OpenPMF) involves five parts:
1. Policy Configuration from the Cloud: Policy configurations are provided as subscription-based Cloud service to application development tools. Offering specification, maintenance, and update of policy models as a Cloud service to application developers and security experts has significant benefits:
Most importantly, instead of having to specify (or buy and install) and maintain the policy models used for model-driven security on an on-going basis, application developers and security specialists can now simply subscribe to the kinds of policy feeds they require without the need to know the details of the models.
The Policy as a Service provider (typically different from the Cloud provider) takes care of policy modeling, maintenance, and update. Other benefits are that the user organization does not need to be a security and compliance expert because the up-to-date policy models will be provided as a feed to them on an on-going basis, that the upfront cost hurdle is minimized thanks to the subscription model, and that there is no need by the end user organization to continually monitor regulations and best practices for changes.
2. Automatic Technical Policy Generation in the Cloud: The automatic policy generation feature of MDS is integrated into the development, deployment, and mashup tools (to get access to functional application information).
It consumes the policy feed described in the previous section. Platform as a Service (PaaS) sometimes includes both Cloud hosted development and mashup tools and a Cloud hosted runtime application platform. In this case, automatic technical policy generation using model-driven security (MDS) can also be moved into the Cloud, so that technical security policies can be automatically be generated for the applications during the Cloud hosted development, deployment and/or mashup process.
This is in particular the case for mashup tools, because those tools are more likely to be Cloud hosted, are often graphical and/or model-driven, and are concerned with interactions and information flows between Cloud services. If the development tools are not hosted on the PaaS Cloud, then the MDS technical policy auto-generation feature needs to be integrated into the local development tools.
3. Automatic Security Policy Enforcement in the Cloud: Policy enforcement should naturally be integrated into the PaaS application platform so that the generated technical policies are automatically enforced whenever Cloud services are accessed.
As described in the previous section, policies are either generated within Cloud using hosted MDS and PaaS development tools, or are uploaded from local MDS and development tools. How policy enforcement points are built into the PaaS application platform depends on whether the PaaS application platform (1) allows the installation of a policy enforcement point (e.g. various open source PaaS platforms, e.g. see case studies below), (2) supports a standards based policy enforcement point (e.g. OASIS XACML), or (3) supports a proprietary policy enforcement point.
4. Automatic Policy Monitoring into the Cloud: Policy enforcement points typically raise security related runtime alerts, especially about incidents related to invocations that have been blocked. The collection, analysis and visual representation of those alerts can also be moved into the Cloud.
This has numerous benefits: Incidents can be centrally analyzed for multiple Cloud services together with other information (e.g. network intrusion detection). Also, an integrated visual representation of the security posture across multiple Cloud services can be provided, integrated incident information can be stored for auditing purposes, and compliance related decision support tools can be offered as a Cloud service.
5. Automatic Updating: The described model-driven approach enables automatic updates of technical security policy enforcement and auditing whenever applications and especially their interactions, change. The same automation is possible when security policy requirements change.
Publications about this can be found in the ISSA Journal October 2010 and on IBM developerWorks. Contact me if you would like to know more information about Policy as a Service.
It is also important to note that model-driven security (MDS) does not necessarily rely on model-driven development to work – even though it relies on application, system, and interaction models (so-called “functional models”) to achieve significant security policy automation.
The traditional MDS approach is that these functional models ideally come from manually defined application models authored during model-driven development (e.g. UML, BPMN). But this is not necessary. We have designed an additional solution for our OpenPMF where the functional models are in fact obtained from an IT asset management tool that is part of our partner’s (Promia, Inc.) intrusion detection/prevention product Raven. This works well, and enables the use of model-driven security in environments which do not support model-driven development or where model-driven development is not desired.
While this may not sound like a big deal, it is in fact a big deal, because it increases the widespread applicability of model-driven security dramatically, and makes adoption a lot easier.