Businesses today have more than ever a sharp focus on reducing capital and operational expenses. Business Process Outsourcing (BPO), Knowledge Process Outsourcing (KPO) and adoption of shared service models have all increased on a global scale. This results in an emerging complexity and volatility of business relationships. As the future internet of services evolves towards dynamic "service marketplaces", where shared services are discovered, negotiated and choreographed at run-time, the new approaches to the compliance management in complex environments are needed. We argue that one of the key issues to address is trust. This paper describes the compliance management models in emerging outsourcing environments that include use of shared services such as cloud computing services. In this context, we briefly present MASTER project that, among other things, integrates several mechanisms to increase the trust levels among stakeholders. Finally, we present a solution for the automated evidence collection at the service provider site and discuss related trust issues.

Traditionally, security patterns have successfully been used to describe security and dependability (S&D) solutions, making them available to system engineers not being security experts. Recently, in the SERENITY research project, the notion of S&D pattern was extended to exact specifications of re-usable S&D mechanisms for Ambient Intelligence (AmI) systems. SERENITY is focused in AmI systems, but its results can be applied to other computer paradigms: grids, distributed computing, etc. SERENITY S&D patterns include information about both the S&D properties that the solution satisfies and the requirements on the context conditions. Along this paper, we describe how abstract S&D solutions can be implemented by means of functional S&D services. In order to do that, our approach is based on the use of SERENITY S&D patterns, and their implementations, called ExecutableComponents. Finally, we propose several examples and we prove their potential application to AmI scenarios.

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