Big Data and Cloud Computing

All of the media, both “mainstream” and “tech”, has gushed over all of the new appliances and devices that are now in the category of what we would call the Internet of Things.  Items like home security,  home lighting, and refrigerators, to name a few. There are many advantages to having connected appliances and devices, Threats that can and will be exploited if unsuspecting users don’t secure them.   Two “layers” of security : The first layer of offering  is a security API that will provide [a way] to easily do a virtual patch, to prevent a remote attack, for example . . . the third layer is cloud: IoT cannot do anything without the cloud.  Most data is sent to the cloud and you will need to have proper protection and make sure the cloud is always available. In both situation Users are vulnerable, mostly due to their own apathy.  Users often either don’t know how to patch their own machines (and in this case, devices) or have glanced...

Organizations make key information security mistakes, which leads to inefficient and ineffective control environment. High profile data breaches and cyber-attacks drive the industry to look for more comprehensive protection measures since many organizations feel that their capability to withstand persistent targeted attacks is minimal. But at the same time, these organizations make some key information security mistakes, that jeopardize their efforts towards control robustness. Although many firms invest in security technologies and people, no one has the confidence that the measures taken are good enough to protect their data from compromises. Below are the 10 worst mistakes which are common to find, and important to address in the path of mature information security posture. If you analyze the cyber security scenarios, and organizational capabilities, the prevailing trend is a vendor-driven approach. In many cases, security professionals adopt the attitude of procuring...

Display useful information from your Windows 10 IoT Core application in an ASP.NET Core web app, essential for integrating IoT data into a solution. Windows 10 IoT background task talk with a web application using WebSockets. Problems As my path to this solution has been troublesome, I am listing here the main problems I faced so my dear readers have a better idea of dead-end streets along the way: I was not able to make the ASP.NET Core web application run under a Windows 10 IoT background service. I found no information about when or if it will be supported in the near future. ASP.NET MVC and ASP.NET Core have different SignalR implementations. I was not able to make a SignalR client for .NET Core work with SignalR hosted on a web application. I was able to make things work by directly using a WebSocket. It’s not as nice a solution as I had in my mind, but it works until things get better. Making the Background Task and Web Application Talk I worked out sim...

Want to get your ASP.NET Core apps working on Windows 10 IoT Core? Here's what you need to know using ASP.NET Core 2 and some minor hacking. It has been problematic to run  ASP.NET Core  applications on  Windows 10 IoT Core , as it is not an officially supported scenario yet, and many components we are used to are not built with Windows 10 ARM in mind. Still, it easy to run web applications on Windows 10 IoT Core using ASP.NET Core 2. There are few tricks developers should know when building web applications for Windows 10 IoT Core. A few things to mention before getting our hands dirty with the real stuff: ASP.NET Core on Windows 10 IoT Core is not officially supported yet. There is only .NET Core runtime available for Windows 10 on ARM, but no SDK (yes, there is no dotnet restore and dotnet build, etc., available). Not all things that work on your dev box will work on Windows 10 IoT Core, and some of these things come out when trying to run a web application ...

StreamSets Data Collector Edge is a lightweight agent used to create end-to-end data flow pipelines. We'll use it help stream data collected from a sensor. Due to the increasing amount of data produced from outside source systems, enterprises are facing difficulties in reading, collecting, and ingesting data into a desired, central database system. An edge pipeline runs on an edge device with limited resources, receives data from another pipeline or reads the data from the device, and controls the device based on the data. StreamSets Data Collector (SDC) Edge, an ultra-lightweight agent, is used to create end-to-end data flow pipelines in StreamSets Data Collector and to run the pipelines to read and export data in and out of systems. In this blog, StreamSets Data Collector Edge is used to read data from an air pressure sensor (BMP180) from an IoT device (Raspberry Pi3). Meanwhile, StreamSets Data Collector is used to load the data into Amazon's Simple Storage Service ...