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Return on investment (ROI) is an important factor for new technology purchase decisions. However, having invested in many security and network… Continue reading
To choose between native and third-party low-code tools, cloud application development teams need to weigh the benefits of consolidation against the risk of lock-in.
s the adoption of no-code and low-code platforms grow, some… Continue reading
Implementing better network segmentation to improve security is a significant project for network operations, data center ops, and security teams. From dividing IoT from IT using micro-segmentation to avoiding over-segmentation, we call out best practices for maximizing success in this task.
• The segmentation requirements for an enterprise call for a highly customized design.
• Avoiding either over-segmenting or under-segmenting the network is achievable but requires a formal project.
• Outsourcing segmentation project planning tends to result in poor outcomes. Too often, trust is placed in less trusted components, often resulting in segmentation projects being delayed or restarted, or with results that place the enterprise at undue risk.
• Segment based on data sensitivity, location, and criticality.
• For virtualized environments, change the technology, but not the security principles.
• Create a segmentation architecture that will accommodate short-term technology changes, and will best allow for housing new resources, applications and data within the existing framework.
• Create zones to proactively house Internet of Things (IoT) and operational technology (OT). Continue reading
IT managed services based on cloud computing are catching on with many small and medium-sized businesses as a way to offload the burdens of buying and maintaining software and hardware.
The idea is simple: instead of buying and managing your own IT assets, your company pays to use a system owned by a third party. A simple free version of the idea is Google Drive, which allows users
anywhere to work and collaborate on word processing, spreadsheet and other applications hosted on Google’s servers.
The cloud’s key benefit is that it saves companies money because they don’t have to purchase, implement, maintain and update hardware or software. For example, some experts estimate a company can save about 65% on an ERP system by implementing it through the cloud rather than buying the software.
The top three IT initiatives for 2018 include business intelligence, artificial intelligence, and big data, according to 451 Research. Digital transformation
Public clouds are the future of enterprise big data analytics, and their use is creating the unified platform needed to fully gain its value.
Today’s big data analytics market is quite different from the industry or even a few years ago. The coming decade will see change, innovation, and disruption ripple through at every segment of this global industry.
In the recently published annual update to its market study, Wikibon, the analyst group of SiliconAngle Media, found that the worldwide big data analytics market grew at 24.5 percent in 2017 from the year before. (I work for Wikibon.)
This was faster than forecast in the previous year’s report, owing largely to stronger-than-expected public cloud deployment and utilization as well as accelerating the convergence of platforms, tools, and other solutions. Also, enterprises are moving more rapidly out of the experimentation and proof-of-concept phases with big data analytics and are achieving higher levels of business value from their deployments.
Going forward, Wikibon forecasts that the overall big data analytics market will grow at an 11 percent annual growth rate by 2027, reaching reach $103 billion globally. Much of the market growth in later years will be sustained by the adoption of big data analytics in the internet of things (IoT), mobility, and other edge-computing use cases. Continue reading
Machine learning isn’t only in the cloud. Microsoft is bringing it to PCs in the next Windows 10 release. Here’s how to get started now.
We’re not far away from a new release of Windows 10, and with it plenty of new APIs for your applications. One big change is support for running trained machine learning models as part of Windows applications, taking advantage of local GPUs to accelerate machine learning applications.
Building a machine learning application can be a complex process. Training a model can require a lot of data, and a considerable amount of processing power. That’s fine if you’ve got access to a cloud platform and lots of bandwidth, but what if you want to take an existing model from GitHub and run it on a PC?
Trained machine learning models are an ideal tool for bringing the benefits of neural networks and deep learning to your applications. All you should need to do is hook up the appropriate interfaces, and they should run as part of your code. But with many machine learning frameworks and platforms, there’s a need for a common runtime that can use any of the models out there. That’s where the new Windows machine learning tools come into play, offering Windows developers a platform to run existing machine learning models in their applications, taking advantage of a developing open standard for exchanging machine learning models. Continue reading
Cloud-native apps built on Kubernetes can run anywhere. Now, with Open Service Broker, they can also use services hosted in public clouds such as Azure. – Cloud Software Development 
Back in the early 2000s, while working as an architect in an IT consulting company, I became fascinated by the promise of service-oriented architectures. Taking an API-first approach to application development made a lot of sense to me, as did the idea of using a message- and event-driven approach to application integration.
But that dream was lost in a maze of ever-more complex standards. The relatively simple SOAP’s take on remote procedure calls vanished as a growing family of WS- protocols added more and more features.
It’s not surprising, then, that I find much of what’s happening in the world of cloud-native platforms familiar. Today, we’re using many of the same concepts as part of building microservice architectures, on top of platforms like Kubernetes.
Like SOAP, the underlying concept is an open set of tools that can connect applications and services, working in one public cloud, from on-premises systems to a public cloud, and from cloud to cloud. It’s that cross-cloud option that’s most interesting: Each of the three big public cloud providers does different things well, so why not build your applications around the best of Azure, AWS, and Google Cloud Platform? Continue reading
As users increasingly demand frictionless authentication everywhere, biometrics solutions have garnered significant attention for both authentication and fraud prevention — especially on mobile and IoT devices. Furthermore, as their
adoption increases, they will hasten the demise of the industry’s least user-friendly method — passwords.
Several newer modalities, such as behavioral and electrocardiogram biometrics, show potential via mobile or continuous authentication, but they face stiff competition from established modalities such as fingerprint, face, and voice biometrics that are also going mobile.
As you strive to provide users with a frictionless registration and authentication experience, make sure the solution performs at scale with an acceptable level of false positives and negatives.
To ensure user acceptance and compliance, you have to reduce the likelihood that biometric samples will suffer a compromise. To this end, use vendors that store only a subset of encrypted mathematical characteristics and parameters of biometric samples. Continue reading
Technology has spawned a dizzying array of new technology security risks with complicated names such as phishing, social engineering and pretexting. Knowing about these new technology risks is already half the battle when trying to
avoid these pitfalls.
Phishing is the use of fraudulent emails or phone calls to get sensitive information, such as bank account numbers, credit card information or passwords. Here is how it works:
If you’ve ever gotten an email that says your account has been locked or that irregular activity was detected in your account, you may have been the target of a phishing attempt. These messages typically include a link to a legitimate-seeming website, where you’re asked to give account information or download malware (see more on that below).
A phishing email or phone call may ask you to call a number to discuss a problem with your account. You might then be asked to reveal account details over the phone.
Phishing is a type of social engineering, which is an attack that uses misrepresentation to get sensitive information.
Pretexting involves the creation of a fake identity or scenario to fool a person into disclosing information.
For example, a fraudster may email or call your company claiming to be a supplier, survey firm, municipal inspector or insurance company to get sensitive data. A pretext attacker could also pose as a computer technician responding to a call for service to access your network.
“They may ask for little bits of information that don’t raise red flags,” Abdulmughnee says. “But over time, bit by bit, they’re trying to build a profile that could let them steal your identity.” Continue reading