How confident are you that passwords are enough to protect your data as a consumer? Michael Nadeau, senior editor at CSO magazine, believes the best thing you can say about using a password for authentication is that it’s better than nothing. High-profile breaches like Equifax, however, have exposed millions of passwords and user IDs, calling into question even that faint praise. Consumers should assume that at least some of their passwords have been compromised. Otherwise, they create a dangerous false sense of security.

If you’re still not convinced about the seriousness of password vulnerabilities, consider these points from the Verizon Data Breach Investigations Report:

• Hacking still accounts for the largest percentage of data breaches.
• Eighty-one percent of hacking-related breaches involved either stolen or weak passwords.

Password-only protection is permanently broken, and any organization relying on it is placing its business and reputation at risk. Even if they avoid a breach, awareness of the shortcomings of password protection is much higher now thanks to Equifax. If that’s how you protect customers’ data, they will think twice about trusting you with it.

Authentication Alternatives

Alternatives like two-factor authentication (2FA), multifactor authentication (MFA), behavioral analytics, and biometrics have been available for some time, but adoption rates are low. The growing threat of breaches and consumer awareness is lowering barriers to implementing these options — primary barriers being user resistance, complexity and ROI.

All these alternatives can be compromised, some more easily than others. Dustin Heywood, senior managing consultant for IBM’s X-Force Red security testing team, shared that all authentication (such as a fingerprint, a face, an iris scan) are broken down into bits and bytes, and they are basically a “shared secret.” Because these shared secrets are stored digitally like a password, it is theoretically possible to steal them. The difference is that it’s harder to do so.

The goal is to make it so difficult to gain access that most cybercriminals will look elsewhere for easier pickings. Many companies use a combination of authentication methods depending on the risk, user considerations and value of the data being protected to reach a reasonable expectation of security.

While consumers might be more accepting of more complex authentication to protect health and financial data due to recent high-profile breaches, not all service providers offer the option. “A lot of banks, because of work that was done quite some time ago, think that having security questions tied to an account is a second factor, which it really isn’t,” says independent security researcher Jessy Irwin. “People want an extra layer of protection, and don’t have the option to turn anything on. They have to go to customer service or an account representative or up a chain to even ask for these features.”

Robert Block, senior vice president at intelligence-based authentication provider SecureAuth, thinks the challenge of implementing stronger authentication is not with the technology. It is about getting decision makers to determine the level of acceptable risk, the number of factors to support and the way to present those factors to the end user.

Whether it is a smartphone or something else, requiring ownership of a device for access limits the damage a cybercriminal can do. Harry Sverdlove, co-founder/CTO of Edgewise Networks, believes the most reliable scheme would require something users know (password, answers to security questions), something they have (smartphone, token device), their location, and something they are (biometrics, behavioral analytics).

If you want your data as a consumer to be better protected, companies need to think beyond passwords. Creating more obstacles for a cybercriminal makes it more likely this individual will move on to another target.

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Ryan Lahti is the managing principal of OrgLeader and author of The Finesse Factor. Stay up to date on Ryan’s STEM organization tweets here: @ryanlahti

(Photo: Password, Pixabay)

If you peruse business publications or pay attention to business commercials for a few minutes, you’re likely to find artificial intelligence (AI) come up in the discussion. It is one of the most used terms today. Although we may not yet have the robots and devices depicted in science-fiction, AI-driven solutions are not hype. According to a recent PwC survey of 1,000 US business executives at companies that are already investigating or implementing AI, 20 percent said their organizations plan to implement AI enterprise-wide in 2019.

Matt Bornstein (principal at VC firm Blumberg Capital) explains the progression to AI. Prior to AI, “explicit programming” had been integral to everything from the mainframe to the smartphone, from the internet boom to the mobile revolution. Basically, it entails thinking deeply about a problem, coming up with a clever approach (i.e., algorithm) and giving a machine a set of instructions to execute. It has helped create new markets and made companies like Apple, Microsoft, Google and Facebook household names.

Since then, we have seen some interesting innovations. For example, Microsoft’s translation engine surfaced which can match human levels of accuracy in Chinese-to-English tasks. Startups are breaking new ground in areas like intelligent assistants, industrial automation and fraud detection.

Deep Learning

The core breakthrough behind each of these advances is deep learning, an AI technique inspired by the structure of the human brain. What started as a relatively narrow data analysis tool now serves as something close to a general computing platform. It outperforms traditional software across a wide range of tasks and may finally deliver the intelligent systems that have long eluded computer scientists.

Amid the deep learning buzz, though, many observers miss the biggest reason to be optimistic about its future: deep learning requires coders to write very little actual code. Rather than relying on preset rules or if-then statements, a deep learning system writes rules automatically based on past examples. A software developer only has to create a “rough skeleton,” to paraphrase Andrej Karpathy from Tesla, then let the computers do the rest.

In this new world, developers no longer need to design a unique algorithm for each problem. Most work focuses, instead, on generating datasets that reflect desired behavior and managing the training process. Pete Warden from Google’s TensorFlow team pointed this out as far back as 2014: “I used to be a coder,” he wrote. “Now I teach computers to write their own programs.”

Autocorrecting Bad Processes

Tom McKeown (CEO and Co-Founder of TrenData, a leading provider of people analytics software) offers a perspective on AI as it relates to enterprise resource planning (ERP) software. He describes ERP software as an application that can efficiently automate manual processes. On the low end, that can be something as simple as a spreadsheet, which automates minor calculations by inputting and copying formulas to multiple cells. A more advanced application might be a type of recruiting software that replaces the repetitive activities of collecting resumes and moving job candidates through the hiring process.

The biggest problem with automating a manual process occurs when that process is a bad one. An example would be if the previously mentioned recruiting software were to track multiple instances of candidates, located somewhere specific, who were recruited through a certain job board and constantly failed a logic test after the fourth interview. In a manually constructed process, that anomaly would go unnoticed for multiple rounds before a human resource information system analyst printed a report and brought it to someone’s attention. Even when fortunate enough to have that analyst, the cost of hours spent interviewing and system uptime to that point would, in most instances, be considerable.

This is where AI and machine learning platforms can provide such great value. The technology embeds the capability for software applications to correct bad processes within the program. If the above candidate scenario were run on an AI-based platform, after the scenario had been run a few times, the system would flag the process, adapt and start rerouting candidates from the job board and location. So, they either don’t advance or more diligence is done at an earlier stage in the process.

Natural Language Processing

One other prevalent use of AI in business software is in the realm of natural language processing. This is where rather than navigating through a series of complex menus, system users can get to the information or section of a program they need by typing a command in the manner they would speak it. Instead of stepping through a hierarchical software workflow, a user would simply type in something like “Where am I getting my best hires?” Then, just like typing a question into Google or any other browser, the answer or a ranking of answers would appear.

By putting AI and deep learning into software-defined architectures, Fierce Telecom argues network operators and enterprises can move a lot of the human manual processes into automated operations in the near term. The long-term goal is moving from automated elements to closed loop automation and finally to autonomous control of networks.

With AI-driven solutions, the software you use will become smarter, more efficient and user-friendly over time. Consequently, future use will involve fewer manual mistakes that cost time and money.

Related articles:

How Much AI Is in Insurance?

Artificial Intelligence and Deep Learning Aid Cancer and Stroke Diagnostics

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Ryan Lahti is the managing principal of OrgLeader and author of The Finesse Factor: How to Build Exceptional Leaders in STEM Organizations being published in early 2019. Stay up to date on Ryan’s STEM organization tweets here: @ryanlahti

(Photo: Machine Learning and AI, Flickr)

In the Las Vegas Renaissance Hotel, two service robots—both Relay robots from San Jose-based Savioke—are quietly at work. These robots, named Elvis and Priscilla, are full-time employees of the hotel.

Are these the only robots? No. Savioke founder Steve Cousins says his company currently has robots in 70 hotels, including the two at the Renaissance. In IEEE Spectrum, Renaissance Hotel manager Carl Krueger explains, “Guests are almost shocked” to see a robot at the door. “We don’t tell them ahead of time that a robot will be making their delivery. They typically open the door and freeze for a moment. Then they’ll read the instructions, push a button—and often giggle.”

These armless robots can’t actually knock. Instead, they robo-call the hotel room and tell the occupant that a delivery is waiting at the door. Elevators are also a challenge—one of the hotel elevators has been adapted to allow the robots to communicate with it wirelessly.

Your Neighborhood

You will find robot delivery in more places than hotels. In January, Amazon submitted a patent application for a sidewalk rolling robot. Amazon wants its robot to carry items from a delivery truck to a person’s front porch, or even bring them into a house. It’s part of a wider effort to solve the perennial last-mile problem for any company trying to deliver goods to your door, one that self-driving vehicles are expected to solve over time. Amazon’s patent application describes a robot that has the technological capability to open doors or garage doors, which isn’t far off a trend that Amazon is already pushing with Amazon Key.

If that isn’t enough to get your attention, two former top executives of Google’s self-driving car project, Jiajun Zhu and Dave Ferguson, think robotic vehicles that deliver only goods can be ready this year. They believe this, because they are the two co-founders of California-based Nuro. Their startup is building an initial fleet of six unmanned electric vehicles about half the size of a passenger car to carry groceries, food orders, flowers, packages and boxes to homes and businesses in urban and suburban neighborhoods.

Nuro has tested conventional vehicles equipped with its autonomous drive software and hardware in California since 2016 to work the kinks out, but is shifting its focus to the small, battery-powered models that look like rolling storage cabinets. While the vehicles aren’t designed to drive on the highway or at high speed, deploying them in other areas such as public roads is dependent on federal and state regulations that are still being finalized.

“By custom-designing vehicles that are specifically for goods transportation you can actually create the safest vehicle on the road,” Ferguson told Forbes. “That vehicle will care about the most vulnerable road users more than it will care about anything that it’s carrying. It can literally choose to run into a tree rather than hit a pedestrian because it knows one of those is a strictly safer outcome than the other.”

The San Francisco Board of Supervisors may perk up their ears at Ferguson’s comment. In December, the board voted to severely restrict delivery robots that roll on San Francisco sidewalks. Now, startups will have to get permits to run their robots under strict guidelines in particular zones, typically industrial areas with low foot traffic. And even then, they may only do so for research purposes, not making actual deliveries. It’s perhaps the harshest crackdown on delivery robots in the United States.

As these events indicate, robot delivery will continue to become a sign of the times. In fact, a report by McKinsey predicted autonomous vehicles in a variety of forms would deliver around 80 percent of all purchased goods in the future. So, you may be sharing your sidewalks, streets and hotel hallways with numerous, non-human forms of delivery sooner than you think.

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Ryan Lahti is the founder and managing principal of OrgLeader. Stay up to date on Ryan’s STEM organization tweets here: @ryanlahti

(Photo: Food Delivery Robot, Flickr)

If you are on the verge of upgrading or getting a new smartphone, do you do it now or do you wait until the “latest and greatest” are available? This is a hard decision since there always seems to be something “greater” coming soon. To help you resolve this dilemma, consider the latest offerings from Google, Samsung and Apple—the Pixel 2 XL, Galaxy Note 8 and iPhone X. Because of the release dates for the Pixel 2 XL and iPhone X, CNET and other reviewers have found it difficult to test them against the fully-reviewed Galaxy Note 8. Nonetheless, here are some key factors to think about regarding each phone based on information gathered to date.

Screen Size

Consumer preferences and behavior are changing as content and connectivity stretch the size of screens. Mobile subscribers are streaming entertainment and using wireless data at an accelerating pace. Content is virtually unlimited and data bundles keep growing. These elements helped to drive the increase in screen size.

Slim bezels and screens that take up almost the entire face of the phone are in, and the combination is giving large-screen handsets a smaller footprint overall.

CNET used a screen-to-body-ratio calculator to find out which of the three phones gives you the most screen in the smallest package. The calculator uses the screen size, screen resolution, height and width to determine the percent of the phone face that makes up the display.

Pixel 2 XL

• 76.71 percent

Galaxy Note 8

• 82.76 percent

iPhone X

• 81.51 percent

Camera Technology

Camera quality is one of the main reasons people buy one phone over another. While CNET couldn’t  compare image quality among these phones yet, it did dig into the camera specs.

Notably, the Pixel 2 phones have one rear camera, not two. Google claims its tech is so good on the single 12.2-megapixel shooter it doesn’t need a second lens. It can achieve the same depth-effect portrait mode with one camera. Photography test site DxOMark gave the Pixel 2 camera its highest rating ever, at 98. The Galaxy Note 8 scored 94. DxOMark hasn’t rated the iPhone X yet.

Meanwhile, Apple’s iPhone X stands out because its camera adds a dramatic portrait lighting effect to enhance depth-effect photos. This is a beta feature on the iPhone 8 Plus and iPhone X.

The Galaxy Note 8, the first Samsung phone with dual cameras and portrait mode, has an effect that saves a wide-angle version of the image along with the telephoto portrait shot. As a result, you get both with the snap of a lens. The iPhone X and Pixel 2 XL will also save two versions of the image, but the exact format is yet to be tested.

Battery Life and Storage

The following battery life information for the Pixel 2 XL and iPhone X are figures from their respective companies. Galaxy Note 8 battery life information is based on CNET testing. As for storage, all three phones start at the 64GB level.

Pixel 2 XL

• Battery: 3520 mAh battery, up to 7 hours with a mix of talk, data and standby use
• Storage: 64GB or 128GB

Galaxy Note 8

• Battery: 3300mAh, 17 hours, 30 minutes (based on CNET testing)
• Storage: 64GB, 128GB (may vary by country and carrier)

iPhone X

• Battery: 2716 mAh, 21 hours talk time, 12 hours Internet use and 13 hours video
• Storage: 64GB or 256GB

Bonus Extras

Each phone has some unique qualities that could play a part in your decision.

Pixel 2 XL

• Squeezable frame launches Google Assistant and silences incoming calls
• Blends optical image stabilization and digital image stabilization to produce smooth video
• Auto-hotspot with Pixelbook laptop

Galaxy Note 8

• S Pen stylus comes bundled with the phone
• Curved screens with specialized shortcut software
• Headphone jack

iPhone X

• Face ID to unlock the phone*
• Portrait lighting mode
• Slow-sync camera flash

*According to Forbes, Apple analyst Ming Chi Kuo says Apple has run into significant problems mass producing the ‘TrueDepth’ camera sensor the iPhone X uses for its Face ID facial recognition system. As a result, iPhone X availability will be extremely limited until 2018.

Cost

These phones start at the mid-$800 range and peak above the $1000 mark. Here are the full retail prices of the phones at launch:

Pixel 2 XL

• $849 (64GB) and $949 (128GB)

Galaxy Note 8

• AT&T: $950, Verizon: $960, T-Mobile: $930, Sprint: $960 (64GB)

iPhone X

• $999 (64GB) and $1149 (256GB)

If you are determined to get one of these new smartphones ASAP, you now at least have key information for making this decision. If you are a little more cautious, it might be worth waiting a couple months until the early-adopters have had a chance to use and share their experiences with the devices.

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Ryan Lahti is the founder and managing principal of OrgLeader. Stay up to date on Ryan’s STEM organization tweets here: @ryanlahti

(Photo: iPhone X, Pixabay)

When Apple opened Siri to developers last year, that was the first step in making the voice assistant a viable competitor to Google Assistant, Alexa and Cortana. This month, Apple allowed developers to help Siri manage to-do lists, take notes, display QR codes and more according to Wired.

Even though Siri already resides in 375 million iPhones, iPads and Macs, Apple is more aggressively inserting Siri into your life. Before, Siri cooled its heels until you summoned it. Apple wants to make it a little more proactive. A new “Siri face” on the Apple Watch will display things Siri thinks you need to know—calendar appointments, reminders, the apps you check most frequently. Siri will watch as you browse the web, building a profile of your interests and activity to make it more useful in recommending articles and sending notifications.

With iOS 11, Siri evolves into more than a voice assistant. It pervades everything that happens on your device, whether you notice or not. When you open Mail, Siri sorts it so the important stuff appears up top. Siri can handle real-time translation, a remarkable achievement even in the few languages it supports. Siri keeps all your data in sync across devices, and works everywhere you need it.

The clearest indication of Apple’s increased confidence in Siri is the new HomePod smart speaker. In-home voice assistants are difficult to get right. They must handle multiple voices, often talking over each other and any background noise. They must respond clearly and correctly, because people quickly grow impatient with a system that doesn’t work. Yet this 7-inch tall speaker—which Wired reported sounds brighter and louder than a Sonos Play:3 or an Amazon Echo—will soon play prominently in people’s homes. It features some controls on the device, and you can use AirPlay to select music, but it’s very much a Siri machine. All this is happening now, because voice recognition and natural-language processing only recently achieved the accuracy and reliability required.

Apple tried to approach Siri as holistically as possible. Rather than do absolutely everything half-well, forcing users to learn a complicated vocabulary (“Alexa, let me talk to Nest”), Apple tried to go deep and then wide. It has been working on teaching Siri how to understand a user’s intent, what the person meant to say and not necessarily the specific words. It wants Siri to only do things it could do well. That hasn’t always panned out, of course—lots of people sneer at Siri because for a long time it couldn’t even handle basic tasks. Now, at least Apple believes it can. And as a result, Siri is starting to conquer the space on, in, and between all of your devices.

The Established Competition

What about Google Assistant? Google Assistant is Google’s latest iteration of an assistant. It’s considered an upgrade or an extension of Google Now – designed to be personal – as well as an expansion of Google’s existing “OK Google” voice controls.

For anyone who has been using an Android device for some time, you know that the Google Now feature quickly pulls out relevant information for you. It knows where you work, and it knows your meeting locations and travel plans, the sports teams you like and what interests you. This data is presented to you in cards and through reminders on your Android device.

Google first unveiled Assistant at Google I/O in May 2016. The company launched it on the Google Pixel and Pixel XL phones, brought it to Google Home and then Android Wear 2.0. At the Google I/O 2017 developers conference, Google confirmed it plans to roll out Assistant as a separate iOS app. Although Google Assistant is becoming a multi-platform voice assistant, it won’t work like it does on Android devices due to API restrictions.

Amazon and Google are thinking along the same lines. Amazon is planning to bring its talkative voice assistant to your iPhone and Android smartphone, according to a high-ranking executive. Currently, the Alexa smartphone application is more of a utilities app to help you manage your skills, profile, etc. The new app will bring Alexa capabilities to your smartphone.

Perhaps you’re curious about new Alexa capabilities on the Echo. With Amazon’s new Speech Synthesis Markup Language that the company introduced last month, Alexa can now whisper, vary its speaking speed, and bleep out words. You can also make free phone calls to other Echo or Alexa app users.

For Cortana fans who want something like Echo or Google Home, you should be pleased that Microsoft has partnered with Harman Kardon to create Invoke. So, you will soon be able to voice control your music and smart home, make and receive hands-free calls with Skype and get answers to your questions on a Cortana-based device. Unfortunately, the release date has not been announced yet. You have to register your email with Harmon Kardon to find out when Invoke will be available.

Voice assistants continue to make everyday tasks a little easier by doing them for us or entertaining us while we do them ourselves. Whether you prefer Siri, Alexa, Cortana or Google Assistant, you definitely have some new enhancements to explore.

Related posts:

Apple and Google Vie with Amazon for Your Smart Home

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Siri Gets Passive Aggressive, Flickr)

Microsoft will do very well with its incoming Teams product that leverages all of Microsoft’s Office 365 apps and services according to new research from Spiceworks. Based on input from 450+ IT professionals in North America and EMEA, the tech company appears set to become kingpin when it comes to messaging platforms in the work environment.

TechRadar noticed two functions that Teams has over the competition. First, when you create a message, you can deem it as “Important” with an exclamation point symbol, alerting everyone in the channel. Second, Teams offers a custom polling tool to easily take team members’ reactions to a given idea, subject, etc. without a plug-in.

Microsoft Teams is only used by 3 percent of businesses right now (this increases to 7 percent when talking about larger firms of 500+ employees), but it’s expected to grow considerably within the next two years, with 17 percent of organizations planning to adopt the system. TechRadar believes this means within two years Teams will be used by 20 percent of organizations (with the majority of that adoption coming in the first year). This would overtake both Google Hangouts and Slack, which Spiceworks estimates will be 19 percent and 17 percent respectively.

In other words, Microsoft Teams will be the second most-used messaging platform, behind only Skype for Business which will be deployed by 47 percent of firms in two years’ time (and is already used by 36 percent of businesses). Of course, that’s a Microsoft product too, leaving the firm pretty dominant when it comes to collaborative chat in the workplace.

As for Workplace by Facebook, another big name in this arena, it is currently only being used by 1 percent of smaller firms, and 2 percent of larger companies. According to Spiceworks, 82 percent of the professionals surveyed said they had no plans to deploy this platform at their organization.

Other interesting points the research turned up include the fact that 47 percent of the EMEA IT pros indicated that they believed collaborative chat apps were critical to the success of their business. When it came to security, respondents weren’t too concerned. Only 32 percent believed that messaging apps put business data at more risk, and 29 percent said that these messaging platforms represent a security risk which is ‘difficult to manage’.

Not to be outdone, Google is bolstering its communications offerings with the addition of Meet according to TechRadar. The full title of the app is Meet by Google Hangouts. This is a videoconferencing solution aimed at providing businesses with meetings that benefit from HD video.

Just as with Hangouts, you’ll be able to make group video calls, although in this case with up to 30 people taking part (triple the number allowed in Hangouts). Although Meet hasn’t been officially launched yet, TechCrunch spotted the product via its website which is now online.

The iOS app did go up for a short time, during which TechCrunch grabbed some details, including the fact that Meet will allow people on the move to use dial-in numbers – but this will only be available to G Suite Enterprise Edition users. Incidentally, the fate of Hangouts remains unclear in terms of whether it will stay as a video chat solution for consumers.

For more information, check out these posts:

Microsoft Teams is the Firm’s App-Filled Answer to Slack and HipChat

Google’s New G Suite Addition Ups the Ante for Videoconferencing

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Microsoft, Flickr)

What do you do if you are the victim of ransomware? For several years, the FBI has recommended that you do not pay when malicious software is used to encrypt or otherwise hold data hostage until a payment is made (a.k.a. ransomware), according to CSO. This position was forcefully echoed by one of the nation’s highest-profile security bloggers – Brian Krebs – in a recent post.

Unfortunately, this advice has not always been followed. The Ponemon Institute reported in a recent study that 48 percent of businesses victimized by ransomware said they paid.

The reality is that the success of ransomware isn’t just increasing. It’s exploding. According to the FBI, the collective amount of ransoms paid in all of 2015 in the U.S. was $24 million. Gartner shared at its 2016 Security & Risk Summit that ransomware is likely to have netted organized cybercrime more than $1 billion in 2016.

The problem is likely worse than the findings. The FBI said many victims don’t report it, “for a number of reasons, including concerns over not knowing where and to whom to report; not feeling their loss warrants law enforcement attention; concerns over privacy, business reputation, or regulatory data breach reporting requirements; or embarrassment.”

The reasons for ransomware’s attractiveness to cyber criminals are not complicated. It doesn’t take all that much expertise – it has been widely reported that it is easy for so-called “script kiddies” to buy or lease the malware on the Dark Web.

A ransomware attack is potentially more damaging than a data breach, especially to a business. No organization wants its data stolen, but it can continue to function after it discovers a breach. If all of its data are encrypted and it doesn’t have a backup, it can’t function.

As a white paper by the Institute for Critical Infrastructure Technology (ICIT) noted, the ransom demanded is generally not a crippling amount. For individuals, it tends to be a few hundred dollars in Bitcoin. “From law enforcement’s perspective, a home burglary results in greater loss than a singular ransomware attack,” the report said, which means law enforcement will rarely devote “significant resources” to investigating it.

According to a recent U.S. Government report, there have been approximately 4,000 ransomware attacks per day in 2016– a dramatic increase over the 1,000 attacks per day reported in 2015. Compared to today’s payment of about 2 Bitcoins or $670 daily, the report estimates the average ransom will substantially increase to be $300,000 per day.

According to ICIT, Joseph Bonavolonta, the Boston-based head of the FBI’s CYBER and Counterintelligence Program, got into trouble with Sen. Ron Wyden (D-Ore.) in October 2015 when he said, “To be honest, we often advise people just to pay the ransom.”

After Wyden complained, the FBI “clarified” that its position was, “only to pay the ransom if mitigation steps failed and the only other option was to lose the files.” Those factors, which all contribute to the success rate of ransomware attacks, are some of the same reasons victims are motivated to pay – they are desperate to recover their files, and they can afford the price more easily than they can afford to lose their files.

Of course, there is plenty of logic behind the FBI’s arguments as well. The primary one is that paying simply makes the problem greater – the more criminals make, the more they will attack.

The bureau and others also note that there is no guarantee that criminals will produce an encryption key once the ransom is paid, or get rid of the malware on the device, meaning a victim could get victimized again.

Krebs said victims do have options, even if they don’t have a current backup. He recommended contacting two websites – No More Ransom and Bleeping Computer – which provide free solutions to at least some ransomware variants.

Krebs said No More Ransom, which is backed by security firms and cybersecurity organizations in 22 countries, had saved 6,000 victims of ransomware more than $2 million by December 2016.

But that statistic, say other experts, shows that while it is a laudable initiative, it is unlikely to slow the explosive growth of ransomware – $2 million is barely a rounding error in the total being collected by cyber criminals.

Stu Sjouwerman, CEO of KnowBe4 explained that the decision not to pay is not always that easy. He said it comes down to a cost/benefit calculation. “It becomes a no-brainer if you are faced with a failed backup and more than a month of lost data that could shut you down.”

Ed Cabrera, chief cybersecurity officer at Trend Micro, also noted the divide between what should happen and what does happen. “The consensus is clear that paying ‘should’ never be an option,” he said. “However, as companies fail to plan, they are planning to fail when it comes to ransomware attacks. This is obviously a very lucrative business in the Deep Web and is only going to continue evolving to different file types and systems that are very important to companies and consumers.”

Given the previous statistics, it is apparent that many organizations are failing to plan. CSO sees this as puzzling, because ways to prevent ransomware are reasonably straightforward and widely publicized, including on the FBI website. The most important thing is to back up data regularly, and secure the backups – don’t leave them connected to the computers and networks they are backing up – so they can’t also be infected by an attack.

Krebs has his own Three Rules of Online Security:

1. If you didn’t go looking for it, don’t install it.
2. If you installed it, update it.
3. If you no longer need it (or, if it’s become too big of a security risk) get rid of it.

Ransomware is an increasing risk. If your organization has not already taken precautions, it is at least worth putting it on the agenda for your next security meeting.

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Cryptolocker ransomware, Flickr)

Why are you hearing so much about sensors? According to Machine Design, sensors are going to be a critical part of the Internet of Things (IoT). Big Data, neural networks, smart machines, and artificial intelligence all require “source data.” In short, a great amount of the IoT discussion comes down to sensors.

Sensors of all types and sizes will be needed to generate the source data upon which the IoT’s intelligence will largely be built. Companies that make the most progress in the next 10 years in embedding and augmenting their hardware and electronics with data gathering and generating capabilities will likely be the market leaders in the following decade. What exists today is perhaps a tenth of what is coming.

Morgan Stanley echoes the significance of sensors in the near future. It points out that microcontrollers (MCUs), the tiny sensors that enable connectivity and control in all the “things” around us, have now become so inexpensive—at around $1 apiece—that they can be incorporated in just about everything, from industrial machinery and home appliances to wearable devices and even clothing.

In a recent survey of more than 100 key decision-makers who represented automotive, consumer electronics and industrial manufacturing companies, Morgan Stanley Research found that more than 90 percent of them are baking connectivity technologies into their designs. This marks a turning point for IoT, the next generation of personal computing, users and their environment.

Consumers and companies ultimately stand to reap the benefits of this new technology. In the near term, the semiconductor industry could be one of the biggest winners. Every 10 percent increase in connectivity using MCUs could add roughly $1 billion to the chip-making industry.

Given the preceding information, sensors clearly are expected to play a significant role in IoT which helps consumers, companies and industries. However, we should still look at them from an objective viewpoint, because they can mislead. Sensors, like the devices, machines, etc. that incorporate them, can make errors.

As Martin Willcox of Teradata points out, sensors sometimes lie. This often comes as a big surprise to business and IT people who tend to believe everything smart devices record can be assumed to be true, because smart devices never come to work hungover or distracted. Talk to the engineers who build and deploy sensor networks and you will rapidly discover that nothing could be further from the truth.

Willcox illustrates his point about sensor fallibility with heart-rate-monitor and desert-oil-field examples. More specifically, his heart-rate monitor falsely showed – in the middle of a 30-minute treadmill workout – that his heart rate was 70 bpm and stayed exactly that same way for several minutes. With desert oil field sensors, he explained that the extreme temperature range that the sensors endure often leads them to “drift” almost as soon as they are deployed and installed.

Consequently, sensors and sensor data do hold great promise, but they still require pragmatic oversight. Willcox emphasizes you can’t assume that machine-generated data are accurate, complete and consistent, just because they are produced by a machine. Furthermore, don’t assume that a low per-unit cost makes sensors easy to replace if they consistently make errors (i.e., fail). In some cases (e.g., desert oil field sensors), the cost of lost production time needed to replace them may not be so low.

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Arenas of IoT, Flickr)

“Alexa, when will Siri join you in managing devices in smart homes?” The answer to this question may not be too far off. Apple Inc. is pressing ahead with the development of an Echo-like smart-home device based on the Siri voice assistant, according to Bloomberg sources.

Started more than two years ago, the project has exited the research and development lab and is now in prototype testing, said the people who asked not to be identified discussing unannounced Apple projects. Like Amazon Inc.’s Echo, the device is designed to control appliances, locks, lights and curtains via voice activation. Apple hasn’t finalized plans for the device and could still scrap the project.

If a product reaches the market, it would be Apple’s most significant piece of new hardware since the company announced the Apple Watch in 2014. Echo has been a surprise hit, even to Apple engineers working on their competing project, and is already being baked into smart-home systems made by a range of companies. Besides taking on the competition, Apple is looking for a new hot seller to augment the iPhone.

The company is attempting to differentiate itself from Echo with more advanced microphone and speaker technology. Some of the prototypes in testing include facial recognition sensors. Apple has acquired the facial recognition startups Faceshift and Emotient over the past two years, which may help the device act based on who is in a room or a person’s emotional state.

Besides serving as a controller for other smart-home devices, the speaker would theoretically be able to process many of the Siri commands available on the iPhone. For example, users may be able to ask the device to read e-mails, send text messages and Tweets, and stream content from Apple Music. Apple has also considered integrating mapping information into the speaker, potentially allowing the device to notify a user when it’s time to leave the house for an appointment.

Google is trying to get into your house as well. According to Bloomberg, the internet search giant introduced Google Home, a voice-controlled wireless speaker that looks and acts much like the Echo. The device comes packaged with Google’s digital assistant technology, a conversational interface that is becoming increasingly critical to the company as its main business, Search, adjusts to a world without screens. The speaker is integrated with other smart-home devices from Philips, Samsung and Nest, a separate division of Google parent Alphabet Inc.

Google hopes its advanced search and artificial-intelligence capabilities will appeal to more consumers in the nascent market for smart home gadgets. Its new device comes out alongside other products that Google designed in-house — a departure for the company, which has historically worked with hardware partners.

Google has tried its own devices before, the most successful being the Chromecast media streaming stick. Google is pricing Home relatively cheaply, a strategy that helped Chromecast’s popularity. The new speakers will retail for $129 in the U.S. Amazon’s main Echo device sells for $179.99, while a smaller Echo Dot speaker ships for $49.99.

The Telegraph reports that the number of people shopping for smart-home gadgets has increased six fold over the last year. So, it is not surprising that tech giants such as Apple and Google want to join Amazon in the enticing smart-home technology market. Although Alexa was the first houseguest, it looks like she will have to get comfortable sharing the space.

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Cord Not Cord By Mikekuba)

In building out the Internet of Things (IoT), the world is undergoing a transformation where nearly everything will be connected explains PK Agarwal, Regional Dean/CEO of Northeastern University-Silicon Valley and former CTO, in EE Times. The early Internet was a collection of documents. Websites served as online brochures or billboards. The second wave was an Internet of commerce when companies such as eBay and Amazon landed tens of billions of dollars in online sales. With the arrival of social media, the third wave became the Internet of people in which Facebook, for example, connects roughly a third of humanity to generate hundreds of billions of dollars.

Now, we are embarking on the fourth wave, the IoT which promises to dwarf every phase that came before it. The IoT can be defined as a network of physical devices including appliances, vehicles, buildings, warehouses, pipelines and other infrastructure fitted with sensors and actuators that enable the objects to collect and share data with a central controller.

IoT investments will top $6 trillion over the next five years, and some 24 billion IoT devices will be installed by 2020, according to Business Insider. Just this year alone, enterprises will spend $232 billion on initiatives to build out the IoT, according to International Data Corp.

Such market momentum is causing organizations to view IoT as increasingly strategic to their business growth. Yet developing a comprehensive IoT strategy still remains the biggest challenge for industry adoption, according to 46.3 percent of 200 IT professionals surveyed by Northeastern University-Silicon Valley at the recent Sensors Expo & Conference in San Jose, California.

Increased efficiency is the main reason that businesses are investing in IoT development, according to 38.3 percent of respondents, followed by the pursuit of a competitive market advantage (28.4 percent). Other drivers for IoT investment include market share growth (15.9 percent) and cost savings (14.9 percent).

Agarwal believes the best IoT strategy for organizations in the near term is to start with small pilot projects to gain some needed experience with IoT systems until specific business cases can be established and understood. In other words, start small and be prepared to fail, but then learn quickly from setbacks to fine-tune your approach to IoT.

With this in mind, let’s see what a couple companies that people do not historically associate with the Internet or Silicon Valley are doing. The first one is GE. GE is selling off its division that makes refrigerators and microwave ovens. It is now focused on electric power generators, jet engines, locomotives, and oil-refining gear. More importantly, it has made a significant bet on developing software to connect these devices to the Internet. GE believes its opportunity lies in what it calls the Internet of Really Big Things.

In the past five years, GE has hired hundreds of software developers, created its own operating system, and fashioned dozens of applications that it says will make planes fly more efficiently, extend the life of power generators, and allow trains to run faster. GE’s plan is to sell this software to other manufacturers of really big industrial things and to be a top 10 software company by 2020. The company says it had software sales of $5 billion in 2015, a sign that the Internet-of-really-big-things approach should be taken seriously.

Besides GE, Ford is serious about leveraging the potential opportunities IoT offers. Something of a pioneer in connectivity – back in 2012 it devised a system whereby cars could recognize and read out text messages via Bluetooth – the automotive giant has set up a dedicated wearables facility at the Ford Research and Innovation Center in Dearborn, Michigan. The researchers and engineers at the lab are looking into ways for vehicles to exploit data collected by wearable technologies and thinking how drivers can interact with connected devices.

Gary Strumolo, global manager for vehicle design and infotronics in Ford Research and Advanced Engineering explains, “The potential in this [IoT] space is endless. We’re evaluating many different wearable devices and applications – everything from helping to keep Ford drivers healthier and more aware behind the wheel to offering an enhanced customer experience at our dealerships.”

Creating an IoT strategy definitely is new territory for companies. Although it is new territory, companies believe that the potential of IoT beckons for them to put strategies in place. GE and Ford are prime examples.

Related posts:

The Internet of Things Deserves Your Attention

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Ryan Lahti is the founder and managing principal of OrgLeader, LLC. Stay up to date on Ryan’s STEM-based organization tweets here: @ryanlahti

(Photo: Pixabay)