Solving the Dilemma of Mobile App Security.

Mobile applications are becoming essential for any enterprise, but they are also a major security risk.

Dealing with that risk on your own isn’t easy. It can take months of work to build your own security measures for mobile apps.  

As demand for enterprise mobile apps explodes, vulnerabilities to security threats proliferate. In fact, according to a recent study by Gartner Inc., market demand for mobile app development services will outpace available IT capacity to deliver those services five to one by the end of 2017. On the security side, mobile is one of the fastest growing enterprise vulnerabilities. According to another study by Garner Inc., More than 75 percent of mobile apps will fail basic security tests through 2015.

The rapid growth of mobile breaches, as well as the increasing costs per incident, mean that mobile app security has never been more critical.

But building sophisticated data encryption and user authentication into a mobile app takes a lot of time and investment for developers who are increasingly in high demand.

Fortunately, there is a solution. Learn how to secure Cordova mobile apps to meet the highest level industry standard for security in a matter of minutes in a new webinar with Appmobi CEO Mark Stutzman on Thursday, Dec. 17, at 2:00 p.m. EST.

In this webinar, you’ll learn how to add enterprise-grade security at the code level to hybrid HTML5 Cordova mobile apps without wasting precious time in the development process.

Appmobi’s Secure Mobile Platform works with a developer’s existing development tools to add the best security available. The platform offers three different levels of application security to meet your organization’s needs, all of which can be implemented in minutes.   

Register for Thursday’s webinar here to find out more. All registered participants will get a free development and production license. 

Aspire’s Optimizer

When it comes to machine learning, knowing how to get the most out of our computing power is essential for building efficient systems and useful products for market. Here at Aspire we’re proud to have an abundance of inventive minds and pioneering experts in optimization that know how to do just that.

This week we’d like to give special recognition to Aspire’s Chief Architect, Thomas Rogers, for being awarded a new patent that optimizes how Remote Storage-DVR services store videos in the cloud. The patent comes from Rogers’ earlier work in 2014 with a previous employer, Concurrent Computer Corporation.

The patent would allow RS-DVR providers to drastically reduce storage for video content with a new file system that lets individual files share any common elements. In the case of Remote Storage DVR’s, where any given program requires thousands and thousands of copies for each individual user, Rogers’ new system could save vast amounts of storage.

When Cablevision introduced RS-DVR—a DVR service that stores the content in the cloud rather than on an expensive, bulky home device—a consortium of copyright holders sued Cablevision for unlicensed rebroadcasting. Cablevision eventually won the case, but with a caveat: in order for the RS-DVR service to not be a rebroadcast, there must be individual copies of recorded programs for each subscriber. And that has been the law of the land ever since.

With traditional files systems, a single file has its own unique set of bytes, sectors, and blocks for each file, which means that providers like Cablevision had to store thousands of large files for a single recorded program for each subscriber. Rogers’ invention is a new file system that maintains individual files, but the mapping from those files would share sectors and blocks that are the same, so that the raw contents of the file on disk is stored only once to be shared, not duplicated.

“Thus, the legal requirement of separate files for recording is maintained” Rogers says, “but the storage at the disk level is optimized.”

Rogers’ expertise in optimization and inventiveness in systems architecture has made him an essential leader to our core technology department, as they develop machine learning solutions to some of the world’s most pressing problems. Although the insights that machine learning produces can be invaluable, it can also take massive amounts of computing power, and that comes at a cost. At Aspire, Rogers is building on his past success to optimize our processes and predictive models, so we can harness those important machine learning insights with less computing power.

Aspire Model Competition Wrap-up: Here’s What We Learned

Aspire’s data modeling competition, The Battle at the Nostradome, is over. The results are in, the winners announced, and now we have new predictive models to incorporate into Tempo Health’s new mobile app, BGNow, that predicts glucose levels for diabetes patients.

Beyond the useful predictive models that resulted from the contest, the four weeks of competition have also resulted in significant insights about the functionality of Aspire’s machine learning tools.

Many teams in the Aspire community used both PRDXT and A2i software tools for the first time, which not only familiarized them with our sophisticated technology, it also provided invaluable insights into how those tools can be improved.

“Having fresh, objective users allowed us the opportunity to refine the interfaces of both tools to make them more user-friendly and intuitive,” Senior Program Manager Christine Fake says.

Those insights, Fake says, will be leveraged during the development of the BGNow application as well as other applications that Aspire teams develop in the future.

The winners of the competition, Team Spacebar, were first-time users of Aspire’s A2i technology. Brian Rihaly and Luke Brodbeck, both research analysts from our research department, say that A2i made the process of optimization much easier. 

They both took home prizes (an iPad and an iWatch) last week for having the best scoring model during the third week of the competition. Their glucose level predictions showed the least deviation from actual glucose levels. 

One thing is clear from the competition, Rogers says, there are countless ways to attack a complex problem.

“That was made evident by the competitors’ diverse approaches to modeling a blood glucose predictive function,” Rogers says.

Despite the variety of approaches, many of the models throughout the competition achieved accurate predictions, Rogers says, and a few models succeeded in accurately predicting glucose levels 30 minutes into the future and beyond. 

Overall, Rogers says, the results are promising.

“It is expected that a few of the models, including the winner, will be trailed within the application BGNow during a beta test period,” Rogers says. “We’re also anticipating new models to be developed before BGNow goes into product.”

Those models will be added into a library for BGNow.

With a robust library of predictive models to choose from, Fake says, BGNow will automatically choose the best predictive model that’s most appropriate for the user and the situation.

Fake says that teams in the competition produced 7 models that may be incorporated into BGNow’s library.

And the work that was done by all of the teams in the Battle of the Nostradome will pave the way for more efficient development of additional models in the future, Fake adds.

Rogers says that the challenging rules of the competition in combination with A2i’s technical requirements created a common hurdle that all of the teams had to overcome. Overcoming that hurdle has produced new insights into how we can make technical hurdles less burdensome, Rogers says.

And that will lead to more efficient methods for modeling and problem solving in the future.