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Machine Learning: The New High-Tech Focus For Cybersecurity

Derek Klobucher

It’s already been a busy year for cybersecurity, as U.S. President Barack Obama warned NATO allies last weekend to closely monitor their impending elections for the kind of suspected Russian hacking that afflicted the latest U.S. presidential election. And last week top U.S. intelligence directors testified about those hacks at a Senate hearing, where topics included ever more sophisticated cyber-attacks and the growing need to fortify American cybersecurity strategy.

Machine learning — along with solid fundamentals — will likely be a key component of reliable cybersecurity in 2017.

“Criminals are fighting a 21st century war, attacking our critical infrastructure and financial systems using unconventional techniques, while we defend ourselves with antiquated methods,” The Hill stated last week. “All the passwords, tokens and other forms of strong authentication are meaningless if a person is tricked into handing over their credentials, inadvertently installs rogue software on their device that performs certain actions, or unwittingly gives a criminal access to their machine or account.”

These cybersecurity fundamentals have certainly become a failure point, and the unrelenting escalation of cyber-attacks has prompted the Federal Reserve, FDIC and others to propose new standards for cyber-risk management, according to The Hill. In the meantime, some organizations are turning to technology for protection.

Machine learning to the rescue

High-tech cyber-defense will place a new emphasis on detecting attacks, as opposed to simply preventing them, according to Nextgov, which tracks how technology and innovation transform government agencies. Machine learning could see a lot wider adoption — and greater success against cyber-attacks — this year.

“It’s clear [that] hackers have refined their art, and are outpacing enterprise security defenses,” Nextgov stated last month. “Machine-learning based solutions … will become more mainstream in 2017, as companies seek to become smarter — and faster to identify and respond to threats.”

Behavioral analytics, for instance, could help organizations use their own data to identify suspicious behavior within automated processes, such as verifying identities and machine-to-machine interactions, according to Nextgov. Based on successful interdictions, machine learning would then improve flexibility and efficiency in managing, investigating and responding to new threats.

Behavioral analytics, for instance, could help organizations use their own data to identify suspicious behavior within automated processes, such as verifying identities and machine-to-machine interactions, according to Nextgov. Based on successful interdictions, machine learning would then improve flexibility and efficiency in managing, investigating and responding to new threats.

But today’s machine learning won’t be enough.

High-tech security solutions can only protect organizations to a point. Likewise, passwords, tokens and other measures only work when users are diligent and savvy.

Machine learning new tricks

To maximize detection efforts, technology must move beyond the common pre-execution machine learning, which only analyzes files before they run, according to the Government Technology Agency of Singapore. In contrast, high-fidelity machine learning analyzes files before and during execution, when malicious code often reveals itself.

“This allows systems to study malicious files in greater detail to better anticipate future threats,” security software provider Trend Micro’s Dhanya Thakkar stated in GovTech last month. “To reduce false positives, high-fidelity machine learning utilizes noise-cancellation techniques … [that] identify known data and applications so that detection technologies can divert precious IT resources into scanning for unknown threats.”

This forward-looking technology has a lot of potential when employed alongside other measures to secure e-mail, mobile and other assets, according to Thakkar. But, as high-fidelity machine learning goes mainstream, cyber-criminals will continue looking for ways to defeat it — and they’re also turning to machine learning.

Up in arms race

“Security is an arms race, and cybercriminals are fine-tuning their methods with the help of machine learning,” McAfee Labs’ 2017 Threats Prediction stated. “It is clear that a considerable amount of research is conducted before the attacks are initiated … [and] we believe that cybercriminals are leveraging machine learning to target victims for BEC and similar scams.”

Business Email Compromise (BEC) “and similar scams” involve social engineering, in which cyber-criminals trick their victims into handing over confidential or private information — or money. These cyber-scams are increasingly sophisticated in order to improve the likelihood of their success; this includes timing attacks to correspond with the mark’s business travel.

Though high-tech cyber-attacks are increasingly sophisticated, basic security measures will still prevent many attacks.

“Tools to perform the complex analysis behind target selection are readily available, and there are a plethora of public sources of data required to build and train malicious machine learning algorithms,” McAfee stated. “Looking to 2017 and beyond, we might even see purveyors of data theft offering ‘Target Acquisition as a Service’ built on machine learning algorithms.”

Back to basics

The fundamentals haven’t changed much.

“If you have anything of value, you have been penetrated,” former CIA and NSA director Michael Hayden said at the SAP Retail Forum 2013. “You’ve got to survive while penetrated — operate while someone else is on your network, wrapping your precious data far more tightly than your other more ordinary data.”

Going back to the basics won’t solve everything. But it can be a big help.

“Most incidents are not the result of a sophisticated, never-before-seen, unpreventable attack,” Data Privacy Monitor stated last month. “[Often] paying better attention to basic security measures would have prevented the issue.”

In short, there’s still no substitute for good cybersecurity fundamentals, “the passwords, tokens and other forms of strong authentication” that The Hill mentioned. So, as we rightly focus on machine learning and other high-tech forms of protection, we must also remember that diligent, savvy people are often still our best line of cyber defense.

This story originally appeared on SAP’s Business Trends. Follow Derek on Twitter: @DKlobucher

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About Derek Klobucher

Derek Klobucher is a Brand Journalist, Content Marketer and Master Digital Storyteller at SAP. His responsibilities include conceiving, developing and conducting global, company-wide employee brand journalism training; managing content, promotion and strategy for social networks and online media; and mentoring SAP employees, contractors and interns to optimize blogging and social media efforts.

Will The Collaborative Economy Completely Reimagine Tomorrow's Big Business?

Daniel Newman

Today, the largest car rental and hospitality companies are Uber and Airbnb, respectively. What do they have in common? Let’s see — neither of them own physical possessions associated with their service, and both have turned a non-performing asset into an incredible revenue source.

Don’t be surprised, because this is the new model for doing business. People want to rent instead of own, and at the same time, they want to monetize whatever they have in excess. This is the core of the sharing economy. The concept of earning money by sharing may have existed before, but not at such a large scale. From renting rooms to rides to clothes to parking spaces to just about anything else you can imagine, the sharing economy is rethinking how businesses are growing.

What’s driving the collaborative economy?

The sharing economy, or the collaborative economy, as it’s also called, is “an economic model where technologies enable people to get what they need from each other—rather than from centralized institutions,” explains Jeremiah Owyang, business analyst and founder of Crowd Companies, a collaborative economy platform. This means you could rent someone’s living room for a day or two, ride someone else’s bike for a couple of hours, or even take someone’s pet out for a walk—all for a rental fee.

Even a few years ago, this sort of a thing was unthinkable. When Airbnb launched in 2008, many people were skeptical, as the whole idea seemed not only irrational, but totally stupid. I mean, why would anyone want to spend the night in a stranger’s room and sleep on an air bed, right? Well, turns out many people did! Airbnb moved from spare rooms to luxury condos, villas, and even castles and private islands in more than 30,000 cities across 190 countries, and rentals reached a staggering 15 million plus last year.

What is driving this trend? Millennials definitely play a role. Their love for everything on-demand, plus their frugal mindset, makes them ideal for the sharing economy. But the sharing economy is attractive to consumers across a wide demographic, as it only makes sense.

How collaborative economy is reshaping the future of businesses

Until recently, collaborative-economy startups like Uber and Airbnb were looked upon as threats. Disuptors to any marketplace are usually threatening, so this isn’t surprising. Established businesses that were accustomed to the way things had always been did (and still do) rail against companies like Uber or AirBnB, yet consumers seem to love them. And that’s what matters. Uber has faced many harsh criticisms, yet it continues to provide more than a million rides a month.

We are living in an era of consumer-driven enterprise, where consumers are at the helm. Perhaps this is the biggest reason why the collaborative economy is here to stay. No matter what industry, companies are trying to bring customers to the fore. A collaborative business model allows customers to call the shots. A great example is the cloud, which relies on resource sharing and allows users to scale up or down according to their needs.

Today, traditional businesses are participating in a collaborative economy in different ways. Some are acquiring startups. General Motors, for example, invested $3 million to acquire RelayRides, a peer-to-peer car sharing service. Others are entering into partnerships like Marriott, which partnered with LiquidSpace, an online platform to book flexible workspaces. Other brands, like GE, BMW, Walgreens, and Pepsi are also stepping into the collaborative-economy space and holding the hands of startups instead of competing with them.

Changes in the workplace

Remote work and telecommuting has taken off as companies become more comfortable with the idea of people working outside their offices, and cloud technology is enabling that. Now, let’s look at the scenario from the lens of the sharing economy. With companies looking to find temporary resources that can meet the fast-changing demands of the business, freelancers could replace a large chunk of full-time professionals in future. Why? Because at the heart of this disruptive practice lies the concept of sharing human resources.

As companies set out to temporarily use the services of people to meet short- and medium-term goals, it’s going to completely change the way we build companies. Also, as we have seen through the growth of companies like Airbnb and Uber, it’s going to change the deliverables that companies provide. With demand changing and technology proliferating at breakneck speed, it’s not just important that businesses start to see and adopt this change; it’s imperative because companies that over-commit to any one thing will find themselves obsolete.

When it comes to workplaces, so much is happening today that it’s impossible to predict where things are ultimately headed. But one thing is for sure: The collaborative economy is not going anywhere as long as our priorities are built around better, faster, more efficient and cost-effective.

Want more insight on today’s sharing economy? see Collaborative Economy: It’s Real And It’s Disrupting Enterprises.

This article was originally seen on Ricoh Blog.

The post Will the Collaborative Economy Completely Reimagine Tomorrows Big Business appeared first on Millennial CEO.

Photo Credit: Pedrolu33 via Compfight cc

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About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

How One Business Approach Can Save The Environment – And Bring $4.5 Trillion To The World Economy

Shelly Dutton

Despite reports of a turbulent global economy, the World Bank delivered some great news recently. For the first time in history, extreme poverty (people living on less than $1.90 each day) worldwide is set to fall to below 10%. Considering that this rate has declined from 37.1% in 1990 to 9.6% in 2015, it is hopeful that one-third of the global population will participate the middle class by 2030.

For all industries, this growth will bring new challenges and pressures when meeting unprecedented demand in an environment of dwindling – if not already scarce – resources. First of all, gold, silver, indium, iridium, tungsten, and many other vital resources could be depleted in as little as five years. And because current manufacturing methods create massive waste, about 80% of $3.2 trillion material value is lost irrecoverably each year in the consumer products industry alone.

This new reality is forcing companies to rethink our current, linear “take-make-dispose” approach to designing, producing, delivering, and selling products and services. According to Dan Wellers, Digital Futures lead for SAP, “If the economy is not sustainable, we are in trouble. And in the case of the linear economy, it is not sustainable because it inherently wastes resources that are becoming scarce. Right now, most serious businesspeople think sustainability is in conflict with earning a profit and becoming wealthy. True sustainability, economic sustainability, is exactly the opposite. With this mindset, it becomes strategic to support practices that support a circular economy in the long run.”

The circular economy: Good for business, good for the environment

What if your business practices and operation can help save our planet? Would you do it? Now, what if I said that this one business approach could put $4.5 trillion up for grabs?

By taking a more restorative and regenerative approach, every company can redesign the future of the environment, the economy, and their overall business. “Made possible by the digital economy, forward-thinking businesses are choosing to embrace this value to intentionally reimagine the economy around how we use resources,” observed Wellers. “By slowing down the depletion of resources and possibly even rejuvenating them, early adopters of circular practices have created business models that are profitable, and therefore sustainable. And they are starting to scale.”

In addition to making good financial sense, there’s another reason the circular economy is a sound business practice: Your customers. In his blog 99 Mind-Blowing Ways the Digital Economy Is Changing the Future of Business, Vivek Bapat revealed that 68% of consumers are interested in companies that bring social and environmental change. More important, 84% of global consumers actively seek out socially and environmentally responsible brands and are willing to switch brands associated with those causes.

Five ways your business can take advantage of the circular economy

As the circular economy proves, business and economic growth does not need to happen at the cost of the environment and public health and safety. As everyone searches for an answer to job creation, economic development, and environmental safety, we are in an economic era primed for change.

Wellers states, “Thanks to the exponential growth and power of digital technology, circular business models are becoming profitable. As a result, businesses are scaling their wealth by investing in new economic growth strategies.”

What are these strategies? Here are five business models that can enable companies to unlock the economic benefits of the circular economy, as stated in Accenture’s report Circular Advantage: Innovative Business Models and Technologies that Create Value:

  1. Circular supplies: Deliver fully renewable, recyclable, and biodegradable resource inputs that underpin circular production and consumption systems.
  2. Recovery of resources: Eliminate material leakage and maximize the economic value of product return flows.
  3. Extension of product life: Extend the life cycle of products and assets. Regain the value of your resources by maintaining and improving them by repairing, upgrading, remanufacturing, or remarketing products.
  4. Sharing platforms: Promote a platform for collaboration among product users as individuals or organizations.
  5. Product as a service: Provide an alternative to the traditional model of “buy and own.” Allow products to be shared by many customers through a lease or pay-for-use arrangement.

To learn more about the circular economy, check out Dan Wellers’ blog “4 Ways The Digital Economy Is Circular.”

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How Emotionally Aware Computing Can Bring Happiness to Your Organization

Christopher Koch


Do you feel me?

Just as once-novel voice recognition technology is now a ubiquitous part of human–machine relationships, so too could mood recognition technology (aka “affective computing”) soon pervade digital interactions.

Through the application of machine learning, Big Data inputs, image recognition, sensors, and in some cases robotics, artificially intelligent systems hunt for affective clues: widened eyes, quickened speech, and crossed arms, as well as heart rate or skin changes.




Emotions are big business

The global affective computing market is estimated to grow from just over US$9.3 billion a year in 2015 to more than $42.5 billion by 2020.

Source: “Affective Computing Market 2015 – Technology, Software, Hardware, Vertical, & Regional Forecasts to 2020 for the $42 Billion Industry” (Research and Markets, 2015)

Customer experience is the sweet spot

Forrester found that emotion was the number-one factor in determining customer loyalty in 17 out of the 18 industries it surveyed – far more important than the ease or effectiveness of customers’ interactions with a company.


Source: “You Can’t Afford to Overlook Your Customers’ Emotional Experience” (Forrester, 2015)


Humana gets an emotional clue

Source: “Artificial Intelligence Helps Humana Avoid Call Center Meltdowns” (The Wall Street Journal, October 27, 2016)

Insurer Humana uses artificial intelligence software that can detect conversational cues to guide call-center workers through difficult customer calls. The system recognizes that a steady rise in the pitch of a customer’s voice or instances of agent and customer talking over one another are causes for concern.

The system has led to hard results: Humana says it has seen an 28% improvement in customer satisfaction, a 63% improvement in agent engagement, and a 6% improvement in first-contact resolution.


Spread happiness across the organization

Source: “Happiness and Productivity” (University of Warwick, February 10, 2014)

Employers could monitor employee moods to make organizational adjustments that increase productivity, effectiveness, and satisfaction. Happy employees are around 12% more productive.




Walking on emotional eggshells

Whether customers and employees will be comfortable having their emotions logged and broadcast by companies is an open question. Customers may find some uses of affective computing creepy or, worse, predatory. Be sure to get their permission.


Other limiting factors

The availability of the data required to infer a person’s emotional state is still limited. Further, it can be difficult to capture all the physical cues that may be relevant to an interaction, such as facial expression, tone of voice, or posture.



Get a head start


Discover the data

Companies should determine what inferences about mental states they want the system to make and how accurately those inferences can be made using the inputs available.


Work with IT

Involve IT and engineering groups to figure out the challenges of integrating with existing systems for collecting, assimilating, and analyzing large volumes of emotional data.


Consider the complexity

Some emotions may be more difficult to discern or respond to. Context is also key. An emotionally aware machine would need to respond differently to frustration in a user in an educational setting than to frustration in a user in a vehicle.

 


 

download arrowTo learn more about how affective computing can help your organization, read the feature story Empathy: The Killer App for Artificial Intelligence.


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About Christopher Koch

Christopher Koch is the Editorial Director of the SAP Center for Business Insight. He is an experienced publishing professional, researcher, editor, and writer in business, technology, and B2B marketing. Share your thoughts with Chris on Twitter @Ckochster.

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In An Agile Environment, Revenue Models Are Flexible Too

Todd Wasserman

In 2012, Dollar Shave Club burst on the scene with a cheeky viral video that won praise for its creativity and marketing acumen. Less heralded at the time was the startup’s pricing model, which swapped traditional retail for subscriptions.

For as low as $1 a month (for five two-bladed cartridges), consumers got a package in the mail that saved them a trip to the pharmacy or grocery store. Dollar Shave Club received the ultimate vindication for the idea in 2016 when Unilever purchased the company for $1 billion.

As that example shows, new technology creates the possibility for new pricing models that can disrupt existing industries. The same phenomenon has occurred in software, in which the cloud and Web-based interfaces have ushered in Software as a Service (SaaS), which charges users on a monthly basis, like a utility, instead of the typical purchase-and-later-upgrade model.

Pricing, in other words, is a variable that can be used to disrupt industries. Other options include usage-based pricing and freemium.

Products as services, services as products

There are basically two ways that businesses can use pricing to disrupt the status quo: Turn products into services and turn services into products. Dollar Shave Club and SaaS are two examples of turning products into services.

Others include Amazon’s Dash, a bare-bones Internet of Things device that lets consumers reorder items ranging from Campbell’s Soup to Play-Doh. Another example is Rent the Runway, which rents high-end fashion items for a weekend rather than selling the items. Trunk Club offers a twist on this by sending items picked out by a stylist to users every month. Users pay for what they want and send back the rest.

The other option is productizing a service. Restaurant franchising is based on this model. While the restaurant offers food service to consumers, for entrepreneurs the franchise offers guidance and brand equity that can be condensed into a product format. For instance, a global HR firm called Littler has productized its offerings with Littler CaseSmart-Charges, which is designed for in-house attorneys and features software, project management tools, and access to flextime attorneys.

As that example shows, technology offers opportunities to try new revenue models. Another example is APIs, which have become a large source of revenue for companies. The monetization of APIs is often viewed as a side business that encompasses a wholly different pricing model that’s often engineered to create huge user bases with volume discounts.

Not a new idea

Though technology has opened up new vistas for businesses seeking alternate pricing models, Rajkumar Venkatesan, a marketing professor at University of Virginia’s Darden School of Business, points out that this isn’t necessarily a new idea. For instance, King Gillette made his fortune in the early part of the 20th Century by realizing that a cheap shaving device would pave the way for a recurring revenue stream via replacement razor blades.

“The new variation was the Keurig,” said Venkatesan, referring to the coffee machine that relies on replaceable cartridges. “It has started becoming more prevalent in the last 10 years, but the fundamental model has been there.” For businesses, this can be an attractive model not only for the recurring revenue but also for the ability to cross-sell new goods to existing customers, Venkatesan said.

Another benefit to a subscription model is that it can also supply first-party data that companies can use to better understand and market to their customers. Some believe that Dollar Shave Club’s close relationship with its young male user base was one reason for Unilever’s purchase, for instance. In such a cut-throat market, such relationships can fetch a high price.

To learn more about how you can monetize disruption, watch this video overview of the new SAP Hybris Revenue Cloud.

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