Tag Archives: Intelligence

Microsoft Security Intelligence Report Volume 22 is now available

The latest volume of the Microsoft Security Intelligence Report is now available for free download at www.microsoft.com/sir.

This new volume of the report includes threat data from the first quarter of 2017. The report also provides specific threat data for over 100 countries/regions. As mentioned in a recent blog, using the tremendous breadth and depth of signal and intelligence from our various cloud and on-premises solutions deployed globally, we investigate threats and vulnerabilities and regularly publish this report to educate enterprise organizations on the current state of threats and recommended best practices and solutions.

In this 22nd volume, we’ve made two significant changes:

  • We have organized the data sets into two categories, cloud and endpoint. Today, most enterprises now have hybrid environments and it’s important to provide more holistic visibility.
  • We are sharing data from a shorter time period, one quarter (January 2017 – March 2017), instead of the typical six months, as we shift our focus to delivering improved and more frequent updates in the future.

The threat landscape is constantly changing. Going forward, we plan to improve how we share the insights, and plan to share data on a more frequent basis – so that you can have more timely visibility into the latest threat insights. We are committed to continuing our investment in researching and sharing the latest security intelligence with you, as we have for over a decade. This shift in our approach is rooted in a principle that guides Microsoft technology investments: to leverage vast data and unique intelligence to help our customers respond to threats faster.

Here are 3 key findings from the report:

As organizations migrate more and more to the cloud, the frequency and sophistication of attacks on consumer and enterprise accounts in the cloud is growing.

  • There was a 300 percent increase in Microsoft cloud-based user accounts attacked year-over-year (Q1-2016 to Q1-2017).
  • The number of account sign-ins attempted from malicious IP addresses has increased by 44 percent year over year in Q1-2017.

Cloud services such as Microsoft Azure are perennial targets for attackers seeking to compromise and weaponize virtual machines and other services, and these attacks are taking place across the globe.

  • Over two-thirds of incoming attacks on Azure services in Q1-2017 came from IP addresses in China and the United States, at 35.1 percent and 32.5 percent, respectively. Korea was third at 3.1 percent, followed by 116 other countries and regions.

Ransomware is affecting different parts of the world to varying degrees.

  • Ransomware encounter rates are the lowest in Japan (0.012 percent in March 2017), China (0.014 percent), and the United States (0.02 percent).
  • Ransomware encounter rates are the highest in Europe vs. the rest of the world in Q1-2017.
    • Multiple European countries, including the Czech Republic (0.17 percent), Italy (0.14 percent), Hungary (0.14 percent), Spain (0.14 percent), Romania (0.13 percent), Croatia (0.13 percent), and Greece (0.12 percent) had much higher ransomware encounter rates than the worldwide average in March 2017.

Download Volume 22 of the Microsoft Security Intelligence Report today to access additional insights: www.microsoft.com/sir.

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AI washing muddies the artificial intelligence products market

Analysts predict that by 2020, artificial intelligence technologies will be in almost every new software and service release. And if they’re not actually in them, technology vendors will probably use smoke and mirrors marketing tactics to make users believe they are.

Many tech vendors already shoehorn the AI label into the marketing of every new piece of software they develop, and it’s causing confusion in the market. To muddle things further, major software vendors accuse their competitors of egregious mislabeling, even when the products in question truly do include artificial intelligence technologies.

AI mischaracterization is one of the three major problems in the AI market, as highlighted by Gartner recently. More than 1,000 vendors with applications and platforms describe themselves as artificial intelligence products vendors, or say they employ AI in their products, according to the research firm. It’s a practice Gartner calls “AI washing” — similar to the cloudwashing and greenwashing, which have become prevalent over the years as businesses overexaggerate their association to cloud computing and environmentalism.

AI goes beyond machine learning

When a technology is labelled AI, the vendor must provide information that makes it clear how AI is used as a differentiator and what problems it solves that can’t be solved by other technologies, explained Jim Hare, a research VP at Gartner, who focuses on analytics and data science.

You have to go in with the assumption that it isn’t AI, and the vendor has to prove otherwise.
Jim Hareresearch VP, Gartner

“You have to go in with the assumption that it isn’t AI, and the vendor has to prove otherwise,” Hare said. “It’s like the big data era — where all the vendors say they have big data — but on steroids.”

“What I’m seeing is that anything typically called machine learning is now being labelled AI, when in reality it is weak or narrow AI, and it solves a specific problem,” he said.

IT buyers must hold the vendor accountable for its claims by asking how it defines AI and requesting information about what’s under the hood, Hare said. Customers need to know what makes the product superior to what is already available, with support from customer case studies. Also, Hare urges IT buyers to demand a demonstration of artificial intelligence products using their own data to see them in action solving a business problem they have.

Beyond that, a vendor must share with customers the AI techniques it uses or plans to use in the product and their strategy for keeping up with the quickly changing AI market, Hare said.

The second problem Gartner highlights is that machine learning can address many of the problems businesses need to solve. The buzz around more complicated types of AI, such as deep learning, gets so much hype that businesses overlook simpler approaches.

“Many companies say to me, ‘I need an AI strategy’ and [after hearing their business problem] I say, ‘No you don’t,'” Hare said.

Really, what you need to look for is a solution to a problem you have, and if machine learning does it, great,” Hare said. “If you need deep learning because the problem is too gnarly for classic ML, and you need neural networks — that’s what you look for.”

Don’t use AI when BI works fine

When to use AI versus BI tools was the focus of a spring TDWI Accelerate presentation led by Jana Eggers, CEO of Nara Logics, a Cambridge, Mass., company, that describes its “synaptic intelligence” approach to AI as the combination of neuroscience and computer science.

BI tools use data to provide insights through reporting, visualization and data analysis, and people use that information to answer their questions. Artificial intelligence differs in that it’s capable of essentially coming up with solutions to problems on its own, using data and calculations.

Companies that want to answer a specific question or problem should use business analytics tools. If you don’t know the question to ask, use AI to explore data openly, and be willing to consider the answers from many different directions, she said. This may involve having outside and inside experts comb through the results, perform A/B testing, or even outsource via platforms such as Amazon’s Mechanical Turk.

With an AI project, you know your objectives and what you are trying to do, but you are open to finding new ways to get there, Eggers said.

AI isn’t easy

A third issue plaguing AI is that companies don’t have the skills on staff to evaluate, build and deploy it, according to Gartner. Over 50% of respondents to Gartner’s 2017 AI development strategies survey said the lack of necessary staff skills was the top challenge to AI adoption. That statistic appears to coincide with the data scientist supply and demand problem.

Companies surveyed said they are seeking artificial intelligence products that can improve decision-making and process automation, and most prefer to buy one of the many packaged AI tools rather than build one themselves. Which brings IT buyers back to the first problem of AI washing; it’s difficult to know which artificial intelligence products truly deliver AI capabilities, and which ones are mislabeled.

After determining a prepackaged AI tool provides enough differentiation to be worth the investment, IT buyers must be clear on what is required to manage it, Hare said; what human services are needed to change code and maintain models over the long term? Is it hosted in a cloud service and managed by the vendor, or does the company need knowledgeable staff to keep it running?

“It’s one thing to get it deployed, but who steps in to tweak and train models over time?” he said. “[IBM] Watson, for example, requires a lot of work to stand up and you need to focus the model to solve a specific problem and feed it a lot of data to solve that problem.”

Companies must also understand the data and compute requirements to run the AI tool, he added; GPUs may be required and that could add significant costs to the project. And cutting-edge AI systems require lots and lots of data. Storing that data also adds to the project cost.

Microsoft Office Users Are Getting AI, But May Not Know It

Over the past few years, Microsoft has quietly added a number of artificial intelligence (AI) features to Office 365 , but my guess is that most Office users either don’t know these features exist, or just take them for granted.

At last year’s Ignite conference, I saw a number of new AI features, and among these were notable new features for PowerPoint and Outlook. But this year, many of those features have deepened and a variety of new tools have been added, some announced at the recent Inspire conference and others announced just this week.

Kirk Gregersen, who heads the program management team within Office, explained that the team’s goal is to add “intelligence into the product in a way that users don’t have to understand to benefit from [it].” This involves using a lot of information the company has in the form of its “knowledge graph”—all of the information you store in documents and email, including what some companies have agreed to share with Microsoft—as well as taking advantage of both the cloud and the AI experience. “Without the move to the cloud, we couldn’t be doing what we are doing,” Gregersen said, explaining that many of these concepts have been around since the 1980s or 90s, but that they weren’t possible without all the data that is now in the cloud.

Gregersen said the product team now works deeply with Microsoft Research, led by executive vice president of Artificial Intelligence & Research Harry Shum, in a way that it couldn’t have in the past. Gregersen referred to these new AI features as “gifts from Harry’s org” and said they have enabled scenarios the product teams have envisioned for years.

Some of the new features are fairly obvious, such as the “focused” inbox in Outlook, while others are less noticeable. (Note again that not every user has all these features yet. I’ll recap the update policies at the end of this post.)

Word Tackles Writing Style

In recent months, Word has added a variety of new proofing tools. The spelling and grammar features have been significantly enhanced, and they have a notably different look.

Among the changes are suggestions that are based in part by contextual ranking, and a “read aloud” feature, which is designed to help those with visual impairments.

Most obvious is the new “gold squiggle,” which suggests style changes within your documents. Each new monthly release adds more of these features, which range from general style critiques to helping you make sure you use more inclusive language, such as identifying gender-specific terms or terms that have different geopolitical meanings. Many of these are turned off by default at present, so users may not be aware they exist. (These settings are listed under File, Options, Proofing, Writing Style as shown in the graphic below). They are interesting and potentially quite useful tools.

Gregersen said this represents a use of AI wherein it takes something that was solely rules-based and adds context awareness. In the future, he said, it will be easier to see how this could be used in LinkedIn resumes, as well as become more personalized, so you could have it ignore certain style issues.

PowerPoint Turns Text into Presentations

Many of the most interesting features involve PowerPoint. Last year, Microsoft demonstrated a new option called Designer, in which PowerPoint can take a variety of slides you have and show you alternatives for different designs based on your content.

In new versions, Designer has improved how it does image analysis in the background, and this helps it to recognize salient regions of a photo, for things like facial recognition (so it doesn’t crop out faces), or extracting color to help determine the color tone for the rest of a presentation. In addition, the company is tracking which designs people choose, and using a ranking algorithm similar to that used by the Bing search engine to propose the most appropriate choices.

My favorite new feature involves taking the text you type and automatically turning it into a visual, or typing a number of steps in a process and turning that into a visual process flow. This was unveiled last year (under the name “SmartArts”), and the company has been updating it over time.

Similarly, another new feature turns a bulleted list with dates into a timeline, and it’s quite cool. It’s long been possible to create such visuals in PowerPoint, but it was time consuming and required a bit of artistic sensibility. This feature makes it much easier.

In addition, last year PowerPoint added a feature called Quick Start, aimed mostly at students, which, if you type in a topic, creates a basic outline of a presentation for you, using information and images from the web that are available under the Creative Commons license. This feature, too, has been enhanced.

Perhaps the flashiest new feature, however, is the ability to translate a presentation into another language in real-time. Presentation Translator was first demonstrated in the

Michael J. Miller is chief information officer at Ziff Brothers Investments, a private investment firm. Miller, who was editor-in-chief of PC Magazine from 1991 to 2005, authors this blog for PCMag.com to share his thoughts on PC-related products. No investment advice is offered in this blog. All duties are disclaimed. Miller works separately for a private investment firm which may at any time invest in companies whose products are discussed in this blog, and no disclosure of securities transactions will be made.

Welcome to the invisible revolution

Think of your favorite pieces of technology. These are the things that you use every day for work and play, and pretty much can’t live without.

Chances are, at least one of them is a gadget – your phone, maybe, or your gaming console.

But if you really think about it, chances also are good that many of your most beloved technologies are no longer made of plastic, metal and glass.

Maybe it’s a streaming video service you use to binge watch “Game of Thrones” on or an app that lets you track your steps and calories so you can fit into those jeans you wore back in high school. Maybe it’s a virtual assistant that helps you remember where your meetings are and when you need to take your medicine, or an e-reader that lets you get lost in your favorite book via your phone, tablet or even car speakers.

Perhaps, quietly and without even realizing it, your most beloved technologies have gone from being things you hold to services you rely on, and that exist everywhere and nowhere. Instead of the gadgets themselves, they are tools that you expect to be able to use on any type of gadget: Your phone, your PC, maybe even your TV.

They are part of what Harry Shum, executive vice president in charge of Microsoft’s Technology and Research division, refers to as an “invisible revolution.”

“We are on the cusp of creating a world in which technology is increasingly pervasive but is also increasingly invisible,” Shum said.

Read the full story.

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