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Big "Mac" Data

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Wednesday, April 3, 2019

Confession: When I was a kid, I ate way too many cheeseburger Happy Meals and played countless hours with Ronald McDonald, that purple lad, Grimace, and the mysterious masked Hamburglar on the old-school playground of yesteryear at McDonalds. 

This trip down memory lane leads me to what “Mickey D’s,” as I affectionally call the fast-food restaurant, is super-sizing on today — machine learning via the acquisition of Dynamic Yield, a Tel Aviv startup that provides algorithmically driven “decision logic” technology. The burger joint will be using this technology to meet and exceed the customer experience with innovation. Here’s how:

We all know the saying “time is money” in this swiftly paced world we live in, so the first deployment of the technology will be in McDonald’s drive thru to speed things up and increase sales. If the drive thru is moving slowly, a digital display could highlight simpler-to-prepare items to speed things up or likewise, when it’s slow highlight more complex-to-prepare, higher-priced food items. While customers grab a French fry out of the bag as they drive off and more fill the drive thru line, algorithms will be noshing on data — weather, time of day, local traffic, nearby events, historical sales data and data from other stores, for example — and then show customers on the display other popular items to prompt potential upsells as they place their order to a voice inside of a box. 

That seems a bit “big brother” in my opinion. I know when I get “hangree,” I’ll order whatever I want, no matter what a digital screen tells me and no matter how long it takes to prepare. But, I digress. 

Beyond the drive-thru, McDonald’s is currently using geofencing around its stores to know when a mobile app customer is approaching and how to prepare their order accordingly. 

The company is toying with the idea of adding the personal touch, turning their mass collection of data into usable information. Think in-store kiosks, mobile order and pay, customers identifying themselves to the store to personalize their hamburger experience, license plate recognition (LPR) that allows the system to identify a specific customer as they approach and adjust the menu based on their specific purchase history, and more. 

Of course, with what sounds like the most glamorous fast-food dining experience ever, I see two major types of risk involved: 

Privacy: The possibility of sensitive data being compromised, like credit card numbers, names, email addresses, phone numbers and real-time location identification is not only real but happens daily, threatening physical and financial safety and security.

Ethical issues: There’s a fine line between personalization and suggestive selling/influencing someone to buy something. While McDonald’s could personalize the experience and perhaps quicken the ordering process by displaying previously ordered items in the form of touchscreen ordering, they could also display only the most expensive items previously bought in an effort to increase sales without the customer being the wiser. 

Digital Yield will remain independently operated, even after the McDonald’s acquisition, and according to Wired, the offer was over $300 million, which makes it the restaurant’s largest purchase since its acquisition of Boston Market in 1999. 

I did the math based on the price of a single Big Mac in the Dallas, Texas area being $3.99. Adding this technology will cost McDonald's approximately 75,187,969 in Big Macs.

What other security risks can you think of related to this technology?

New tech holds the key to stopping cybercrime, study finds

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Tuesday, February 12, 2019

You don’t have to look too hard to find a sobering example of cybercrime, as it's as pervasive as ever these days, even on the national level with recent reports that cyber criminals have access to critical infrastructure such as our national power grids and gas lines. The good news, though, is technology may be our best weapon against these invisible criminals.

In fact, the use of big data and blockchain technologies are key to fighting cybercrime, according to a new study from Frost & Sullivan that looks at how effective machine learning is in aiding early detection of cyber anomalies, and how good blockchain is at creating a trustworthy network between endpoints.

Frost and Sullivan noted that the rise of the Internet of Things has opened up numerous points of vulnerabilities, compelling cybersecurity companies, especially startups, to develop innovative solutions to protect enterprises from emerging threats. As cybercrime becomes more sophisticated and even a method of warfare, the research firm found, technologies such as machine learning, big data, and blockchain will become prominent.

"Deploying Big Data solutions is essential for companies to expand the scope of cybersecurity solutions beyond detection and mitigation of threats,” Hiten Shah, research analyst, TechVision, said in the announcement of the findings. "This technology can proactively predict breaches before they happen, as well as uncover patterns from past incidents to support policy decisions."

The study, Envisioning the Next-Generation Cybersecurity Practices, presents an overview of cybersecurity in enterprises and analyzes the drivers and challenges to the adoption of best practices in cybersecurity. It also covers the technologies impacting the future of cybersecurity and the main purchase factors.

"Startups need to make their products integrable with existing products and solutions as well as bundle their solutions with market-leading solutions from well-established companies," noted Shah. "Such collaborations will lead to mergers and acquisitions, ultimately enabling companies to provide more advanced solutions."

Technologies that are likely to find the most application opportunities include:

•    Big Data: It enables automated risk management and predictive analytics. Its  adoption will be mostly driven by the need to identify usage and behavioral patterns to help security operations spot anomalies.
•    Machine Learning: It allows security teams to prioritize corrective actions and automate real-time analysis of multiple variables. Using the vast pools of data collected by companies, machine-learning algorithms can zero in on the root cause of the attack and fix detected anomalies in the network.
•    Blockchain: The data stored on blockchain cannot be manipulated or erased by design. The tractability of activities performed on blockchain is integral to establishing a trustworthy network between endpoints. Furthermore, the decentralized nature of blockchain greatly increases the cost of breaching blockchain-based networks, which discourages hackers.

Envisioning the Next-Generation Cybersecurity Practices is part of Frost & Sullivan’s global Information & Communication Growth Partnership Service program.

News Poll: Data analytics has value in the industry

Most say that operational efficiency and business intelligence are key uses
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04/19/2017

YARMOUTH, Maine—Data analytics and big data are big topics in the industry, coming up at several industry events—but is there value in it?

First stop for biz intelligence? Retail security pros

TechSec 2015: With Big Data, security not just about preventing bad things, but aligning with company goals
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02/09/2015

DELRAY BEACH, Fla.—Leveraging Big Data establishes retail security professionals as business enablers, according to four experts at TechSec2015.

Why managed access gets adopted, why it doesn't

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Wednesday, January 7, 2015

Managed and hosted access control systems, or access control as a service "ACaaS" has been on the rise for some time now. IHS's Blake Kozak put out a research note today with some interesting ACaaS projections.

From the report: "IHS estimates that newly installed hosted and managed access control doors represented about 3 percent of the total new readers and electronic locks installed in the Americas in 2013. A total of about 80,000 doors of ACaaS were added in the region in 2013. IHS has forecast there will be about 1.8 million total doors of ACaaS in the Americas by 2018."  

ACaaS is good for end users and integrators alike, the report points out.

For integrators, it's a source of RMR and it also increases "stickiness" of accounts. For end users, outsourcing access control provisioning and permissions to an integrator removes a major hassle internally. Very important also, is that the fact that ACaas is sold as a service, so the funds come from the operating budget rather than the capital expenditure budget, making it easier for end users to "sell" internally.

However, Kozak notes that it's not always possible to fully fund ACaaS through the OpEx budget. "For example, a system with 100 doors and 400 card users would likely not use a 100% opex model. The integrator/installer will need to obtain some amount of revenue upfront."
    
Kozak also says that "Web-based panels are continuing to experience growth, potentially impacting the adoption of ACaaS."
    
IHS predicts that we'll see more hybrid systems "a mix of onsite management, monitoring and hosted infrastructure."
    
Finally, the note brings up another important topic: Big Data. A buzzword for sure, but if they can figure out how to capture and collate the data efficiently, access control data, like video data, should be in important source for advanced business intelligence in the future.

Integrators: Making money on big security data

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Wednesday, December 11, 2013

When I met with my TechSec advisory board this past summer to talk about TechSec 2014, one of the topics the group wanted to make sure we talked about was big data. We had an excellent primer on big data at TechSec 2013, thanks to Axis’ Steve Surfaro and EMC’s Patrick Snow. For this year’s conference (Jan. 28-29 in Delray Beach, Fla.), we wanted to take a different tack.

I"m really pleased with the idea we came up with. We've asked four leading integrators to discuss how they’re helping their customers mine and synthesize data from their video and access control systems.

Kratos CTO Chris Peckham is going to moderate the educational session that will feature these integrators: David Coleman of Avrio RMS; Nigel Waterton of Aronson Security Group; Robert Locke of Open Innovation (part of Tyco); and, Don Zoufal of SDI.

The discussion will center on how the data is extracted, what kind of business intelligence that data provides and in what format. Each integrator will focus on the data mining they're doing in a specific vertical market including city surveillance, airports and retail.

Sound good? You can register for TechSec here.