In 2016, American businesses suffered half a billion dollars a year in losses from phishing attacks with the average cost at $1.6 million each. These numbers are alarming evidence that just one click can cause significant financial and reputational damage to your brand. And since studies show that a staggering 30 percent of phishing emails get opened, it’s no wonder that they consistently rank as the top cyberattack vector.
Despite being one of the oldest cyberattacks in the book, phishing remains so popular because it’s a highly effective means of exploiting the weakest link in the cybersecurity chain: humans. To make matters worse, hackers have become much more sophisticated in their techniques: no more poorly written, typo-ridden Viagra spam emails and unclaimed heritage scams. Phishing attacks are now highly targeted, dynamic and "hypermorphic," making them increasingly difficult for both humans and machines to detect.
Technology progresses quickly. In large part, that’s due to semiconductors, which power everything from computers to toasters.
As semiconducting components become more advanced, they get smaller and more powerful. This, in turn, enables electronic products to become smaller, more powerful and more cost-effective. One company, which has long been a leader in the semiconductor business, recently introduced a unique machine that takes microprocessor production to the next level.
While the success of Apple Watch has attracted the most attention when it comes to enterprise wearables in the workplace, the market is beginning to split into battles for the wrist (and borrowing from Neil Cybart), the eyes (e.g. Google Glass) and the ears (e.g. AirPods). Not to mention wearables for the body -- smart garments and (God forbid) implantables (Now, apparently, a word. Though if someone in my company tells me I need to implant something for my job, they will have my resignation before they finish the request).
But the adoption of such technology comes with a practical limitation -- we each have only so many wrists and assorted body parts. And let’s not discount the fact people will naturally resist adorning themselves with devices throughout the workday. Nobody wants to walk around the office looking like they’ve just been assimilated by the borg.
First, let’s clarify the difference between Augmented Reality (AR) and Virtual Reality (VR). Virtual Reality (VR) blocks out the real world and immerses the user in a digital experience. Augmented Reality (AR) adds a layer of interactive digital elements on top of the real world. Or in simpler terms, AR can be defined as a technology which overlays a computer-generated image on a user’s view of the real world. The question is: when will we begin to see more Enterprise adoption of AR?
Companies are eager to jump on the AR bandwagon but are still unclear how to best use AR to drive sales around their product, improve efficiencies for their operations. Additional unknowns include how much it will cost to enhance the B2C/B2B experience and when companies could expect to see a return on their investment.
Enforcement of the GDPR Regulation will begin this May 25. Are you ready? If not, Microsoft offers some information-protection solutions to help your organization identify, classify, and protect your data. The tools track your adherence to the regulations, ensure you’re able to identify sensitive data, and can prevent that data from escaping your organization via email, etc.
While this article focuses on GDPR policy management, the info also applies to other regulations (e.g. HIPAA).
The Internet of Things has taken the global tech industry by storm in recent years. The idea, in its simplest form, is the mass interconnectivity of billions of devices. All of this is in the hope that it creates a massive network of devices in constant communication with each other.
Why would this network be important? Because it has the potential to completely revolutionize how we interact with tech and with the world around us. When all of the devices in the world are interlinked then we have the possibility of extracting mountains of data and synthesizing it so that we may make improvements across the board.
Making an app is hard, but getting it noticed on the Apple App Store and Google Play Store can be an even more difficult task. Optimizing your metadata is the biggest hurdle to getting noticed and finding users.
There are many "tips and tricks" articles out there that promise to help, but very few talk about what to avoid. Fortunately, with a strong App Store Optimization (ASO) strategy, you can stand out from the crowd while keeping an eye out for ASO pitfalls. By maneuvering around these pitfalls, you’ll be one step closer to improving your app’s visibility.
No matter the industry, ensuring the security of all our digital transactions is everyone’s biggest concern. Aside from bitcoin and other cryptocurrencies, enterprise blockchain technology has the potential to overcome many current (and potentially future) hurdles digital transactions must face.
So how do organizations determine if blockchain is right for their business? How do companies know when is the best time to implement and start using blockchain? Before we answer these questions, let’s first provide some background on what blockchain is and how it works.
In April, Lastline launched the first of our Malscape Monitor reports, for the fourth quarter of 2017. The report analyzes data from our Global Threat Intelligence Network to provide several insights and benchmarks on encounter rates with malware that CISOs can use to measure their own cyber risk and security performance.
There are three findings that I want to elaborate on in this blog post that I think will illustrate why many of today’s threat detection technologies are ineffective resulting in increased risk of a malware infection.
Conducting a web search on mobile -- unless you’re incredibly specific -- is hit or miss. Want to test it out, just use your device’s voice assistant to conduct a search.
Siri or Google Assistant will commonly return an unrelated series of results, more than they should anyway. Then, you have to sort through lengthy search listings to find what you’re looking for, hopping from website to website until you find what you need. Even then, a single website might not contain the full amount of information you’re looking for. Sorting through the results manually isn’t any more accurate, however. And the smaller the display, the fewer results you’ll be able to sort through, making the process that much more tedious.
When traveling, we like to take as little as possible. We don’t want to be dragging a huge 15" laptop on the road, but we still need access to our files, data and even our favorite apps.
With this in mind, often we carry around a small USB stick with our most important data. Simply plug the USB stick into any computer and you have full and secure access to your files, without having to worry about copying them to the temporary PC.
2017 was the year of DevOps with companies focusing on delivering better customer experience and improving operational efficiency. According to a recent Forrester report, over 60 percent of organizations surveyed said they have either already implemented or are expanding their DevOps efforts in the future. With the rise of DevOps, greater investments in software development and a faster release cadence comes a need to measure the impact of these efforts and ensure they are delivering valuable software faster. To do this, organizations are taking a more modern approach to code deployment, release management, and measurement of outcomes.
This approach known as experimentation is a new product development workflow, combining DevOps and Product Analytics, helping organizations both speed up product delivery while simultaneously providing critical insights on the performance of their features and products. Every feature release is measured against business and technical KPIs defined by the organization. Experimentation teams, historically only formed at leading technology companies, are now emerging in most enterprises who are starting to look for and build out engineering and product experimentation roles.
Over the past year, I’ve spent a lot of time with companies across different industries, listening and working to understand their unique needs. As their respective landscapes evolve, it’s clear that each of them is looking for technology that accelerates the execution of their most imperative objectives. With that in mind, I want to take a look at a few specific industries, examining issues they face as well as their plans for innovating for the future. First up: financial services.
From my perspective, there are three pivotal shifts underway.
Best friends are hard to come by. Once the right one is found, we tend to make conscious choices to invest in those relationships in order to build the right foundation for the future. Unfortunately for many CIOs, it’s a pretty short list of applicants. As organizations change and grow, CIOs will be the resident experts on things like big data, the Internet of Things (IoT) and automation. Not only is this a weighty charge, CIOs are at the forefront of change management, which can feel isolating as they forge new paths.
Now, as automation becomes mainstream, many CIOs are finding an unlikely ally: the robots themselves. But, just like our real-life best friends, it’s important that CIOs choose wisely. By taking the right path to deployment and unleashing the true benefits, CIOs can ensure that their new best friends will be around for the long haul. Here are three ways CIOs can partner with robots to make the most of the relationship.
For almost a decade, most of us using Facebook have trusted it with our personal data. We shared pictures, locations of fun places we visited, friends --old and new -- with whom we connected, 'liked' activities, and much more.
And we did this not knowing our personal information was being used in ways beyond anyone's comprehension. As we watch the Facebook story unfold, we may wonder whether this crisis could have been avoided had personal data privacy and governance been better handled. Such initiatives could be complex and expensive for any company, but is it fair to say there are no shortcuts to this approach? How prepared is any company that relies on personal data?