Microsoft warns wormable Windows bug could lead to another WannaCry

Microsoft warns wormable Windows bug could lead to another WannaCry

Microsoft is warning that the Internet could see another exploit with the magnitude of the WannaCry attack that shut down computers all over the world two years ago unless people patch a high-severity vulnerability. The software maker took the unusual step of backporting the just-released
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New Intel security flaws could slow some chips by nearly 20%

New Intel security flaws could slow some chips by nearly 20%

(Reuters) - Intel Corp and a group of security researchers on Tuesday said they had found a new set of security flaws in its processors that will be difficult to fix and are related to problems found last year. Intel calls the newly discovered flaws
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What Is Edge Computing?

The rise of IoT (the Internet of Things) has led to a renewed focus on Edge computing. Edge is a computing infrastructure that exists at the edge of the network—at or on the actual sources of data. It’s both the compliment to—and the natural evolution of—the cloud infrastructure that many organizations and government agencies are utilizing today.

Today, organizations use the cloud to process the volumes of data generated by a sensor or device in real time. However, this system has its shortcomings and limitations. First, this requires network connectivity, which can be spotty or unreliable at the edge. Next, this slows down the process and fails to make actionable data insights available to those at the edge of the sensor or device that may need it. Ultimately, it lacks the efficiency required by the advanced IoT implementations of tomorrow.

what is edge computing?

Edge computing empowers the sensors at the edge to conduct rapid processing of collected data at the device level. If cloud computing represents a remote server farm, Edge represents what once was the far reaches of the organizational DMZ.

Why does Edge matter?

Let’s say you deploy a sensor whose function is to monitor the depth and cresting height of a river. You probably want it to monitor water levels so you can determine when it’s too low for river traffic to navigate, or be alerted when the river is in danger of reaching flood level. These are pretty straightforward measurements for a device to collect and share.

Edge computing pushes machine learning to that Edge sensor, enabling the “smarter-than-before” sensor to handle more variables and provide much more valuable intelligence.

Take our river sensor as an example. Flood marks exceeded during a rainstorm are more dangerous than a slight rise caused by the spring thaw. Rising water can be bad news to the local population if it isn’t projected and communicated promptly. The more analysis the Edge sensor can do, the more valuable data the sensor consumer receives.

The river example is just one of many that device intelligence at the Edge can manage, but how does it translate for federal agencies and organizations starting to wonder what lies on the Edge?

Edge computing for the federal government

There are many agencies considering, evaluating and designing edge computing solutions. The goal of such a solution would be to move the processing for data analysis closer to the data to speed up data processing.

And this is just one example of what Edge computing can enable for federal agencies. Overall, most organizations could benefit from the computing efficiencies and added intelligence inherent in Edge-driven processing. They could also benefit from the resulting reduction in the number of sensors necessary and the reduction in the amount of data for humans to analyze.

These efficiencies will help to make Edge computing programs more productive and also free up agency staff to focus on more mission-critical tasks instead of analyzing data.

Approaching the Edge

There have been multiple advancements in technology and tools that are enabling Edge computing, and helping to make this level of efficiency a reality. The first involves the continued decrease in cost for computing resources. Today’s sensors are becoming increasingly capable without becoming increasingly expensive because the cost of computing power is decreasing—making these solutions simultaneously more powerful and more accessible.

Next, these sensors are becoming capable of generating more, disparate types of data. Machine learning and analytics feeds on data, and the more data available, the more these technologies are capable of.

Finally, the footprint for computing resources is shrinking. This means that small sensors are capable of doing much more than they were previously. The smaller footprint of these devices and sensors opens the door for an increasingly diverse ecosystem of implementations.

These trends are all aligning to make Edge computing more economical and accessible to federal agencies that may have a use for them. If you think your agency/company could be one of the ones that could benefit from computing at the Edge, there is a process to follow to help make an Edge computing program a reality.

First, you have to identify an area of need where smarter sensors capable of generating actionable intelligence in the field could help your agency or company become more effective or overcome a problem.

Once that problem is identified, your agency should identify a trusted technology partner with the resources necessary to identify the new and emerging technologies on the market and the experience necessary to build an end-to-end solution utilizing a combination of established solutions and emerging technologies.

By Scott Anderson

Scott Andersen

Scott Andersen is the managing partner and Chief Technology Officer of Creative Technology & Innovation. During his 25+ years in the technology industry Scott has followed many technology trends down the rabbit hole. From early adopter to last person selecting a technology Scott has been on all sides. Today he loves spending time on his boat, with his family and backing many Kickstarter and Indiegogo projects.

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