Spring World 2017

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Bonus Journal

Volume 29, Issue 5

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Jon Seals

Jon Seals

I was working with a long-term colleague at a national organization who informed me of his leadership was deciding to build a Business Continuity/Disaster Recovery (BC/DR) solution themselves.  He asked “Should I buy a ready-made solution or do you think it’s feasible that we build our own solution?” This gave me pause before I formulated him my response, which is rare for me.

The questions were more of a self-assessment and reflection on the organization. Does your staff have the time and skill set to design a BC/DR compliant software solution, and can they map needs into the functional components of such a solution? Even if you answer is “yes,” there are still other critical points to consider, which are:



At least 47 of 62 new crypto ransomware families discovered by Kaspersky Lab researchers in 2016 were developed by Russian-speaking cybercriminals.

More than 1,445,000 users were hit by ransomware in 2016, Kaspersky reports.

According to Kaspersky, a flexible and user-friendly ransomware ecosystem is enabling small groups with limited financial resources and technical capabilities to develop into large criminal enterprises.

The researchers say there are three essential levels of criminal involvement in ransomware -- the development and updating of new ransomware families, the creation and support of affiliate programs distributing the malware, and the participation in those affiliate programs as a partner.



Wednesday, 15 February 2017 18:12

Cyber Security Planning

In today’s digital business climate, it’s critical to stay up to date with cyber security. In 2012, FEMA released a presentation “designed to increase understanding of cyber threat alerts, warning, and information sharing across sectors, and to test and evaluate government-private sector coordinating structures, processes, and capabilities regarding cyber event response and recovery.” Emerging technologies from the past five years call for an update of these recommendations, specifically:



Finding the Right System

An emergency notification system is all you need to protect your employees, right? That can be easier said than done. If you’ve been relying on email or phones to inform and alert your employees, you have a little homework to do before you can choose the best emergency notification software for your company. There are many providers out there offering all kinds of features, capabilities, pricing, integrations, and promises, but which ones best fit your requirements?

It’s not easy finding the right technology, but that doesn’t seem to be stopping many organizations. Gartner estimates IT spending will grow 2.7 percent in 2017 and continue at this rate until at least 2020. Where is all of this IT spend going? The majority is spent on communications services, followed by IT services, devices, software, and data center systems, respectively. Nearly $4 trillion dollars have been dedicated to such investments since 2014.



Wednesday, 15 February 2017 18:10

Artificial Intelligence and Data Storage

"My God. It's Full of Data" - Bowman (My apologies to 2001: A Space Odyssey)

Just in case you weren't sure, there is a huge revolution happening. The revolution is around using data. Rather than developers writing explicit code to perform some computation, machine learning applications, including supervised learning reinforcement learning and statistical classification applications can use the data to create models. Within these categories there are a number of approaches, including deep learning, artificial neural networks, support vector machines, cluster analysis, Bayesian networks and learning classifier systems. These tools create a higher level of abstraction of the data, which, in effect, is learning, as defined by Tom Mitchell (taken from Wikipedia):

"A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E."

After learning, these tools can make predictions based on new input data. Rather than create code with sets of rules and conditions to model a problem or a situation, these algorithms utilize only the data to form their own rules and models.