Blog Moved

Future posts related to technology are directly published to LinkedIn

Friday, January 31, 2014

Cloud Architecture Security & Reliability

Yesterday, I was doing a presentation at SSIT, Tumkur on Cloud Architecture Security & Reliability to the faculty members of SSIT and SIT Tumkur.

With the advent of Cloud Computing paradigm there are at least five categories of "Actors" emerged.
1. Cloud Consumers, 2. Cloud Providers, 3. Cloud Brokers, 4. Cloud Auditors, 5. Cloud Carriers. The NIST conceptual reference model gives a nice overview of these. ( )

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The security of more specifically "Information Security" is a cross cutting concern across all these actors. The CSA publishes top threats regularly here. The top threats 2013 are
  1. Data Breaches
  2. Data Loss
  3. Account Hijacking
  4. Insecure APIs
  5. Denial of Service
  6. Malicious Insiders
  7. Abuse of Cloud Services
  8. Insufficient Due Diligence
  9. Shared Technology Issues

All these threats translate to protecting four major areas of Cloud Architecture...

  1. Application Access - Authentication and Authorization
  2. Separation of Concerns - Privileged user access to sensitive data
  3. Key – Management - of encryption keys
  4. Data at Rest - Secure management of copies of data
Interestingly the ENISA threat landscape also points to similar emerging threats related to Cloud Computing -

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Is there any shortcut to achieve security to any of the actors in the Cloud? I do not think so. The perspective presented by Booz & Co on cloud security has a nice ICT Resilience life clycle that was discussed.

Finally, there was a good discussion on the Reliability and Redundancy. The key aspect was how do we achieve better reliability of a complex IT system consisting of multiple components across multiple layers (i.e., web, application, database) to make best utility of non failing components to share the load while isolating the failure component and decoupling it from the cluster and seamlessly re-balancing the workload to the rest of the working components.

Overall it was a good session to interact with academia!

The slide deck that was used:

Friday, January 10, 2014

Social Analytics for Online Communities

This is the first post of 2014. Happy new year to one and all...........

A recent discussion on knome (TCS' internal social platform) related to managing online communities, controlling spam, making the best out of an enterprise social platform of the scale of ~200K members made me study the application of Social Analytics to achieve these objectives.

As I research on the internet, came across this paper - titled "Scalable Social Analytics for Online Communities" by Marcel Karnstedt, Digital Enterprise Research Institute (DERI), National University of Ireland, Galway Email:

This post is to summarize the contents of the paper and some of my thoughts around it.

Success of a social platform depends on strength of analytics understanding and driving the dynamics of the network built by the platform.

To achieve these goals we need to have a set of tools that can perform multidimensional analysis of the structure, behavioural, content/semantic and cross community analysis.

Structural Analysis: Analyse all the communities, memberships, sub-communities based on strong relations between the members, influencers/leaders and followers.

Behavioural Analysis: Analyse the interactions to identify the helpful experts (or sub-groups) who provide information and newbies who are seeking information that are benefited by the interactions. Both a micro-level or individual level and a macro-level analysis is needed.

Content / Semantic analysis: Use text mining to detect, track and quantitatively measure current interest and shift in interest in topic and sentiment within the community.

Cross community dynamics: Understand how the community structure and sub structures are influencing each other to detect redundancies and complementary to merge and link them together.

There is a need to sufficiently combine all the analysis from all four dimensions in a scalable real-time model to achieve best understanding, control and utility of socially generated data. (rather knowledge!)

New solutions for new problems! Have a nice weekend...........