Why do we need mobile intelligence?

It’s easy to talk about big data. It’s not quite so simple, however, to manage billions of pieces of information coming at you each day. How do you make sense of all that input? How do you turn it around into something actionable? More importantly, what individual or team can go through that much content in a timely fashion?

MI:RIAM in numbers

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21,687,777

Unique domains visited

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1,175,105,406

Requests handled

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58,226

Data seen (in GB)

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481,386

High severity threats detected

What does she do?

Powered by 2 billion daily inputs from millions of mobile devices, MI:RIAM continuously analyzes these vast feeds of information to detect and respond to new insights.

Zero day detection

MI:RIAM uses Wandera’s global footprint to identify patterns of risk. This enables Wandera’s mobile security service to identify new leaks and highlight previously unknown vulnerabilities.

Risky app discovery

MI:RIAM is continuously analyzing apps that are installed and the network traffic they generate. This higher-level analysis allows MI:RIAM to identify risky apps before they put the organization at risk.

Data usage optimization

MI:RIAM continually compares company usage patterns, connections and policy to optimize data connections on the fly.

Anomaly identification

Trained on the standard operating procedure of devices, apps, Wi-Fi access points and user groups, MI:RIAM builds a baseline understanding of behavior, then seeks out anomalies.

Instant reactions

MI:RIAM makes informed, intelligent decisions about the security events she encounters enabling Wandera to respond by blocking, filtering and altering in a heartbeat.

Infrastructure risk assessments

MI:RIAM uncovers malicious infrastructures as well as conducting analysis of potentially problematic regions or into the extent of breached devices.

Case Study: Ever heard of SLocker?

MI:RIAM protected thousands of mobile devices against over 400 variants of this vicious trojan malware, while others paid millions of dollars in ransom.

How she works

MI:RIAM not only has access to more data inputs than any other mobile intelligence, but is able to view it from multiple angles, granting her an unusually transparent perspective on mobile data that would simply not be possible with other technologies.

She works by continually analyzing the world’s biggest and most varied mobile dataset, and is powered by a sophisticated blend of machine learning technologies.

inputs

Two billion inputs

User
OS
Device
App
Network Infrastructure
App Store
mobile

Mobile Intelligence

Neural networks

A very broad class of ML algorithms loosely based on imitating a biological brain. Responsible for several recent breakthroughs especially in image processing and language translation.

Clustering

Attempting to divide a set of samples into different groups such that samples in the same group are more similar to each other than samples in the other groups.

Support vector machine

A binary classification algorithm that works by finding the dividing line between two types of samples.

Anomaly detection

A broad class of problems in machine learning and statistics about finding samples that are different from the norm. This can include unusual periods in time, users, apps etc.

Predictive analytics

The field of making predictions about the future based on current data by whatever method – be that machine learning algorithms or statistics.

Markov models

A predictive model in which a system can be in one of a certain number of states and the probability of future states depends only on the current state.

reponse

Response

Zero day detection
Anomaly identification
Risky app discovery
Instant reactions
Data usage optimization
Infrastructure risk assessments

Machine vs. human

Humans are intelligent, but there continue to be things that machines can simply do better than your typical analyst.

Universal focus

MI:RIAM can do all things simultaneously, never needing to prioritize one task over another. She can therefore discover unknowns in the places humans wouldn’t think to look.

Tireless ethic

All MI:RIAM needs to function is data and electricity. She’s never tired and never stops working.

Breakneck speeds

She’s not only far quicker at analyzing data than humans but she’s considerably faster than other automated solutions.

Continuous Improvement

The machine learning technologies that MI:RIAM is built with means she gets better with time, adapting to new inputs and results as she processes them.

Eternal Accuracy

MI:RIAM is never wrong. She’s continuously checking and double-checking her work to ensure absolute accuracy.

Constant connection

MI:RIAM is always connected, meaning her data set is always fresh and actionable. She’s never working with outdated information.

Case Study: Pharmaceutical nightmares

Pharmaceutical nightmares: MI:RIAM detected a rogue internal device attacking its own company from the inside out and going completely undetected by the MDM.

Get MI:RIAM working for your mobile fleet today