Note: this blog is a mirror of my HP Labs Blog, on the same topic, accessible at: http://h30507.www3.hp.com/t5/Research-on-Security-and/bg-p/163

Monday, April 19, 2010

Identity Analytics and Economics of IAM – Presentation at IFIP/IEEE BDIM 2010

Due to recent “volcanic activities”, I could not attend the 5th IFIP/IEEE International Workshop on Business-driven IT Management 2010 - BDIM 2010, Osaka, Japan.

However, I have been able to give a remote presentation of the topic discussed in my accepted paper:

“Marco Casassa Mont, Yolanta Beres, David Pym, Simon Shiu - Economics of Identity and Access Management: Providing Decision Support for Investments”

My full presentation (MS .ppt) is available here. An abstract of the paper (and presentation) follows:

“Identity and Access Management (IAM) is a key enabler of enterprise businesses: it supports automation, security enforcement and compliance. However, most enterprises struggle with their Identity and Access Management strategy. Discussions on IAM primarily focus at the IT operational level, rather than targeting strategic decision makers' issues, at the business level. Organisations are experiencing an increasing number of internal and external threats and risks: there is scarcity of resources and budget to address them all. Decision makers (e.g. CIOs, CISOs) need to prioritise their choices and motivate their requests for investments. This applies for investments in IAM vs. other possible security or business investments that could be made by the organisation. In this context, a range of possible IAM investment options has an effect on multiple strategic outcomes of interest, such as assurance, agility, security, compliance, productivity and empowerment. We have developed a repeatable approach and methodology to help organisations work through this complex problem space and determine an appropriate strategy, by providing them with decision support capabilities. The proposed approach, validated in collaboration with security and IAM experts, couples economic modeling (which explores decision makers' preferences between the different outcomes) with system modeling & simulations to predict the consequences (likely outcomes) associated with different investment choices and map them against decision makers' preferences, in order to identify the most suitable investment options. We illustrate how this methodology has been applied in an IAM case study, in a business-driven context with core enterprise services. This work is in progress. We discuss current results and next steps.”

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