Here are this week’s top stories in telco fraud and big data technology:

SDN, IoT Drive Network Refreshes: Security Lags Behind

The glass is half full: workplace mobility, Internet of Things (IoT) and SDN are pushing enterprises to upgrade their network devices at a faster rate. The glass is half empty: security is being largely forgotten in these transformation processes due to neglected patching. [Mike Robuck, Telco Transformation]

Telecom Industry Continues Push into Cloud Platforms

Cloud platforms along with the move towards virtualization technologies have begun to have a significant impact on the way telecom operators run their businesses. Operators have been very active in providing cloud-based options for customers, as well as have begun to use such platforms to enhance their own operations. [Dan Meyer, RCR Wireless]

The Power of Machine Learning in Cybersecurity

Machine learning is a buzzword that has picked up steam across several industries, and especially in the cybersecurity space we see more and more companies adding machine learning capabilities as a differentiator into their marketing materials. However, machine learning has been around for decades, and many security companies have been using it under the hood for a while. So what is changing, how much is hype and what shows promise? [Daniel Gutierrez, insideBIGDATA]

AI, Sci-Fi, Robots … Roomba

Headlined by household names like Professor Stephen Hawking, most of the attention in the AI debate is trained on the potential threat of artificially replicating human behavior in machines. Can robots make ethical decisions? Can machines sense the world around them? How can we stop mankind being overrun by killer androids? Much of the discussion going on in the AI/machine learning world today suggests that Terminator-type scenarios are a worry we can put on hold for a few years. As Gary Marcus of New York University noted at the recent O’Reilly AI conference, AI is a challenge that we have yet to master. “We wanted Rosie the robot, instead we got the Roomba.” [Mary McEvoy Carroll, Argyle Data Insights]

Lowenstein’s View: The Wireless Industry Is Changing before Our Eyes

There are moments in time where one can sense important shifts going on in an industry. I think now is one of those times in wireless. First, some historical context – what have been the other ‘big shift’ moments? [Mark Lowenstein, FierceWireless]

Analyst Angle: How Did M2M Migrate into IoT?

There’s an old adage in marketing that rapidly expanding markets always segment. A hundred years ago you had the car or automobile, but as the market expanded to cover trucks, buses and other kinds of transportation, the term vehicle came into being that covers all the segments including cars, trucks, buses and all their sub-categories. [J. Gerry Purdy, RCR Wireless]

The Looming Disaster of the Internet of (Hackable) Things

Last January, walking through the seemingly endless showroom at the gadget bonanza known as the Consumer Electronics Show (CES) in Las Vegas, I saw a glimpse of what’s to come. Big multinational brands as well as small startup gizmo-makers were showing off their latest creations in an attempt to sell us their products—and the future. This year, the future, as it has been for the last couple of years, is focused on the internet. But now, specifically, it’s about enabling every object you can imagine with web capabilities—the so-called Internet of Things. [Lorenzo Franceschi-Bicchierai, Motherboard]

Beware Dodgy Data Analysis

Data science is having its 15 minutes of fame. Everyone from John Oliver of HBO’s “Last Week Tonight” to famed election statistician Nate Silver of 538.com is getting on a soapbox about the perils of believing data-based findings that lead to seemingly crazy conclusions. [Xiaojing Dong and John Heineke, CIO]

An Introduction to Deep Learning

Deep learning is impacting everything from healthcare to transportation to manufacturing, and more. Companies are turning to deep learning to solve hard problems, like speech recognition, object recognition, and machine translation…To understand what deep learning is, we first need to understand the relationship deep learning has with machine learning, neural networks, and artificial intelligence. [Charlie Crawford, Algorithmia]

#FraudFriday: Signal Manipulation (SIP and SS7 Hacking)

Just as the Internet runs on TCP/IP and HTTP, the mobile world uses SIP and SS7. Signal manipulation involves manipulation of either the SIP or SS7 signaling message. Traditionally, this form of hacking has been used to hide the true origination or identity of the caller. [Staff, Argyle Data Insights]