Protecting your online privacy is important. There has been a lot of discussion in recent years about how to stay safe online, and an increasing number of people are turning to Virtual Private Networks to keep their browsing data hidden from advertisers and overzealous intelligence agencies.
However, your privacy could still be at risk even behind the protection of a VPN. There are three common vulnerabilities that can leak information about you online: WebRTC and DNS leaks which affect VPN users, and app data leaks which can affect anyone and everyone. Read on to find out more about these three types of data leak, and what steps you can take to prevent them.
The following is an exclusive excerpt from Project to Product: How to Survive and Thrive in the Age of Digital Disruption with the Flow Framework by Dr. Mik Kersten:
Entering the BMW Group Leipzig plant in Germany is an awe-inspiring experience. My hosts are Rene Te-Strote and Frank Schäfer. Frank is a plant manager responsible for overall vehicle integration. The enormous Central Building was designed by architect Zaha Hadid, who designed some of the most unique buildings of our time. The unapologetically sci-fi architecture invokes the feeling of walking into the future. The most prominent sight upon entering is an elevated and exposed section of the production line that towers high above eye level. Car bodies move across a suspended conveyor and then slowly disappear out of view as they glide over a sea of desks. The production line is visible to anyone who enters the building and to all the staff, and the entire building is designed around it. Every part of the building has some practical aspect related to manufacturing and value delivery. Everything embodies the maturity and scale of one of the masters of the Age of Mass Production.
Ever since its conception, 3D printing has represented a significant leap forward in technology. Granted, many people believe there was an excessive amount of hype around 3D printing when the tech first hit markets.
While there were some kinks to work out, however, no one can deny the revolution that swept over almost every industry in the world. The simple idea of creating anything from nearly any material in the comfort of your home or warehouse has meant that suddenly, a lot of middlemen are getting cut out of a job. Yet, for the businesses themselves, 3D printing has been a game-changer and a massive boon to their revenue. The technology managed to affect a lot of industries very differently, but here are a few of them.
The year is 2010. Cloud adoption is growing by leaps and bounds. Soon, everything will be in the cloud, and why wouldn’t it be?
But here in 2019, we know now that the narrative has shifted a bit. Our recent survey, The State of IT Infrastructure Management, only proves that the story is a little more complex than 100 percent cloud: Among organizations moving some of their on-prem infrastructure off-prem within the next three years, nearly four in 10 plan to move to a colocation environment.
The market is saturated with hundreds of security products, and companies spend billions of dollars each year on cybersecurity spend (expected to top $100 billion by 2020). Yet breaches and hacks are still in the news every day, because cybersecurity is such a tough problem. Organizations have a massive and exponentially growing attack surface -- there are a myriad of ways by which networks can be breached. Analyzing and transforming the enterprise cybersecurity posture is not a human-scale problem anymore. An enterprise vulnerability management program is the cornerstone for any modern cybersecurity initiative and helps security teams proactively understand and improve their security posture to avoid breaches and protect the business from brand and reputation damage, as well as loss of customer trust.
Understanding and acting on data output from your vulnerability assessment scanner is a critical component of your vulnerability management program. However, if your scanner is identifying vulnerabilities by the thousands every time a scan completes, your team will soon be left overwhelmed and struggling with how to proceed. Failure to address vulnerabilities in a timely manner due to the high volume of alerts is very problematic. And of course, most of these vulnerabilities are bogus or merely theoretical. Traditional vulnerability management programs leave you drowning in data, but starving for insights.
Employee happiness; it’s a pretty important thing these days. It isn’t just a fluffy, nice-to-have feeling for employees. It’s a business necessity.
Without it, employees don’t feel a strong connection to their employer’s mission and values. And when that happens, it means employees are disillusioned, don’t feel supported and recognised for good work, and are less likely to stick it out long-term with their employers. That’s what I call a recipe for turnover disaster. But in reverse, when employees feel strong mentally and feel like they enjoy working for their employer, it improves morale.
A number of options are available for providing high availability protection for applications running in the Azure cloud. Some of these options are cloud-based services. Some are in the operating system or application software. And some are purpose-built by third-parties. The numerous permutations and combinations available can make it extraordinarily difficult to choose the best and most cost-effective solution for each application.
In general, failover clusters are the best option for assuring high availability. Historically, failover clusters were relatively easy to configure and test in the enterprise datacenter using shared storage and standard features built into Windows Server. But in the Azure and other public clouds, there is no shared storage. This creates a need to find other options for running mission-critical applications in a public or hybrid cloud environment. This article examines the options available for providing high availability (HA) for applications running within the Azure cloud. Special emphasis is given to SQL Server as a particularly popular application for Azure.
If you are like me, there is a good chance that you are confused as well about the most recent terminology to use in the field of data science … pardon, artificial intelligence … no, I mean data science. No, I mean artificial intelligence. Please, somebody tell me what I should call it and what the difference is!
Isn’t artificial intelligence just a new cool name to label the old traditional data science? Don't both concepts cover the same algorithms? And isn’t it all machine learning anyway? This is what I used to think until I took a pause to write this post. During this breather, I went back in time and tried to remember all the names that used to be used to label this field of what essentially is data analytics. Let’s see …
Most organizations are currently in the process of investigating, planning, or deploying artificial intelligence (AI) implementations, but there’s a problem: businesses -- or even AI designers -- don’t understand how or why the AI arrived at a specific decision. This is a big hurdle for businesses who want to begin relying on AI-based dynamic systems for their decision making. In fact, a recent PwC survey found that 37 percent of executives said ensuring AI systems were trustworthy was their top priority, and 61 percent would like to create transparent, explainable, and provable AI models.
The need for transparent, explainable AI goes beyond individual business preferences. Interpretability, fairness, and transparency of data-driven decision support systems based on AI and machine learning are serious regulatory mandates in banking, insurance, healthcare, and other industries. In addition, regulations like GDPR’s right to explanation clause or the upcoming California Consumer Privacy Act will compel businesses to know what their AI algorithms are thinking. The solutions to these issues of trust and explainability typically have been to stick with simpler models, improving transparency at the expense of accuracy. From my perspective, understanding how to create trust -- more so than creating transparency -- in AI is going to be crucial to success.
Widely regarded as the greatest football coach of all time (much to the chagrin of NFL fans outside of New England), Bill Belichick has now 'enjoyed' six Super Bowls as coach of the Pats (plus two more as Defensive Coordinator for the Giants) and led the Pats to three-fourths of AFC Championship games (including a record-setting 8 consecutive trips).
But what’s really made Belichick great is his belief that you shouldn’t just "run what we run," but that you should game-plan specifically for each opponent. This means the strategies and actions they employ are based on what they expect each specific opponent to do. And if things aren’t working as planned, they switch it up and adapt (Belichick is the master of in-game adjustments). Here’s a few examples:
You cannot miss the signs of technological advancement in travel today. From mobile ticketing to biometric scanning at amusement parks, today’s business trips and family vacations look vastly different than in years past. Innovation has come just in time for the crowds -- Expedia Group reported a 40 percent increase in the number of people traveling for business and leisure since 2016, and this number is on track to grow in the coming years.
Behind the scenes, one of the quiet workhorses of hospitality innovation has been the Internet of Things (IoT). Broad and flexible IoT coverage has already enabled major changes in the traveler experience and the hospitality industry, through innovations such as luggage tracking to parking and trash management. Largely in part to communication networks that enable the travel industry to implement a variety of innovative solutions, cheaply.
Every business by now is familiar with the term 'digital transformation', and for good reason. When done right, digital transformation has the potential to revolutionize the customer experience; drive data-based insights; encourage collaboration across departments; increase agility and innovation; update skillsets and knowledge; consolidate processes and operations; and create incredible returns on investment.
So why aren’t more people concerned about it?
While it’s essential that employees consistently avoid taking risks that could lead to a data breach, even top-performing employees don’t necessarily have top-notch cybersecurity knowledge. Thus, organizations are in charge of bridging the cybersecurity skill gap to keep employees from damaging the company’s network by accidentally uploading of a malicious program or sharing confidential documents with the wrong people.
Though it’s easy for IT and leadership teams to put systems in place that defend their network from external threats, well-intentioned internal users can be a hackers easy way in. The only way for organizations to counter this is with education and training.
One of the biggest threats as you browse the internet isn’t hackers trying to get into your computer (a common misconception) or the potential of accidentally installing malicious software. Your security suite should take care of both these issues.
No, the single biggest issue is your personal data and the information you leave all over the internet when you share your content, chat with other people and the login information we use to access our online data. What can we do to safeguard our personal data and keep it away from people seeking to exploit us? Here are our top tips.
Nothing in life is certain except death, taxes, and an article appearing daily in the news either slating or praising millennials. Millennials, or Generation Y, are the group of people who were born between 1981 and 1996. Opinions of millennials range from those claiming that they are everything wrong with our changing society, others that they are saving it. Millennials are arguably the most influential generation of consumers today, making smart, considered decisions all the time.
One such decision is their method of transport. Reports suggest that millennials are buying fewer cars than older generations, with 43 percent of them saying that having a car was a hassle. Cars used to be the ultimate status symbol, so why are so many millennials avoiding them? Is it sustainable living? The rise of Uber and Lyft? Are they holding on for connected cars? Or do they simply just not want to drive?