How to Ensure the Success of Your Privileged Access Management Projects
- LANGUAGE: English DATE: Tuesday, January 19, 2016 TIME: 4:00pm CET, 3:00pm GMT
The majority of 2015's high profile security breaches can be attributed to lost or stolen credentials and nowhere are the stakes higher than with those distributed to “super users”. It’s no surprise, therefore, that many organisations looking to shore up their defences start with privileged access management (PAM).
However, success is not easy to achieve and many PAM projects stall. To avoid this, organisations have to follow a well-planned strategy and know where to begin. What shall be protected? Passwords of shared accounts only? Or also the ones of other accounts with elevated privileges? What about restricting access in administrator sessions or monitoring sessions? And for which systems? Setting the scope and expectations is the starting point for a successful project. But there are more challenges to solve when successfully running PAM – learn about these in this webinar.
This KuppingerCole Webinar provides:
- Information on why organisations do PAM
- Insight in why PAM projects stall
- An Overview of the most common risks in setting up PAM projects
- Case studies: real-world examples
- Recipe for success – top tips
In the first part of this webinar, Martin Kuppinger, Founder and Principal Analyst at KuppingerCole, will explain the reasons why organisations carry out more and more PAM projects in today's fast-changing threat landscape and why they, however, sometimes stall.
Alan Radford, principal solutions architect EMEA with Dell Security, will share in the second part of this webinar the secrets of successfully implementing a PAM solution. He will refer to real-world examples and conclude with helpful recipes for success of PAM projects.
As modern businesses across all verticals continue their rapid digitalization, the need to store, process and exchange data securely is becoming an essential factor for any company. However, this is particularly challenging for high-tech companies dealing with highly-sensitive R&D data.
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