21st century innovation requires new thinking, new tools and the application of a creative mind. When it comes to innovating Operational Risk Management (ORM), take a leap towards "Predictive Intelligence". What has been holding you back? Is it the right combination of new thinking, new tools and the applications you haven't even thought of yet?
How could we apply the use of a High Computing Cluster (HPC) using Amazons Elastic Compute Cloud (EC2) with the right haystack of data to get the answers we seek? Without building a new data center and for under $5K. Think about the possibility of 10,000 plus server instances running across five data centers, with the results we seek in hours. Utility Super Computing is here today for white hats and also even the "Black Hats."
Predictive Analytics is an art and a science, that is thriving with the use of "Fusion Infrastructure" by the hour. Why do we need to spend tens of millions of dollars on our own data center anymore, to get the rapid answers we require to run our business or to defend our nation?
Now the debate has gone beyond the infrastructure, to look at the other bottle necks. What about the database architecture itself? Is the traditional implementation of the disk intensive real-time Relational Database Management System (RDBMS) paradigm over? Hadoop is here, yet requires new language learning curves and is a batch solution. This could be one of the answers to predictive risk innovation:
How could we apply the use of a High Computing Cluster (HPC) using Amazons Elastic Compute Cloud (EC2) with the right haystack of data to get the answers we seek? Without building a new data center and for under $5K. Think about the possibility of 10,000 plus server instances running across five data centers, with the results we seek in hours. Utility Super Computing is here today for white hats and also even the "Black Hats."
Predictive Analytics is an art and a science, that is thriving with the use of "Fusion Infrastructure" by the hour. Why do we need to spend tens of millions of dollars on our own data center anymore, to get the rapid answers we require to run our business or to defend our nation?
Now the debate has gone beyond the infrastructure, to look at the other bottle necks. What about the database architecture itself? Is the traditional implementation of the disk intensive real-time Relational Database Management System (RDBMS) paradigm over? Hadoop is here, yet requires new language learning curves and is a batch solution. This could be one of the answers to predictive risk innovation:
MemSQL is the distributed in-memory database that provides real-time analytics on Big Data, empowering organizations to make data-driven decisions, better engage customers, and discover competitive advantages. MemSQL was built from the ground up for modern hardware to leverage dozens of cores per machine and terabytes of memory. We are entering an era that will be defined by distributed systems that scale as you need capacity and compute, all on commodity hardware.How long will it take you to stand-up your own "Operational Risk Intelligence Center"? One or two days or a week, with the right people and skill-sets in place. What kinds of questions and answers will allow you to predict the future, faster than your competitor or your latest cyber adversary?
At the Black Hat security conference in Las Vegas, a quartet of researchers, Alex Stamos, Tom Ritter, Thomas Ptacek, and Javed Samuel, implored everyone involved in cryptography, from software developers to certificate authorities to companies buying SSL certificates, to switch to newer algorithms and protocols, lest they wake up one day to find that all of their crypto infrastructure is rendered useless and insecure by mathematical advances.
We've written before about asymmetric encryption and its importance to secure communication. Asymmetric encryption algorithms have pairs of keys: one key can decrypt data encrypted with the other key, but cannot decrypt data encrypted with itself.
The asymmetric algorithms are built on an underlying assumption that certain mathematical operations are "hard," which is to say, that the time it takes to do the operation increases proportional to some number raised to the power of the length of the key ("exponential time"). This assumption, however, is not actually proven, and nobody knows for certain if it is true. The risk exists that the problems are actually "easy," where "easy" means that there are algorithms that will run in a time proportional only to the key length raised to some constant power ("polynomial time").
Innovation in the Operational Risk Management spectrum is on the verge of massive change. Operations Security, Fraud Analytics and Supply Chain Management are just the beginning. The Board of Directors of the commercial enterprise, Military Strategic Commands and virtual chat rooms on the deep web, are debating these very subjects. Application of "Utility High Performance Computing" in combination with 4th Paradigm databases, puts innovation back at the forefront of the creative mind.
