Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

Grant Moerschel

Grant Moerschel



App Freedom Vs. Corporate Security

IT has to walk a fine line when securing user-owned mobile devices.

You can't prevent employees from snapping up iPads and Droid phones, even if you wanted to. Sixty-five percent of respondents to our InformationWeek 2011 Mobile Device Management and Security Survey predict that the number of employee-owned devices accessing company data will increase. What you can do is use your leverage when they want to connect to business systems by asking them to run mobile device management (MDM) software, which can enforce corporate policies and provide features such as device tracking and remote wiping.

Even though it's a fair trade, IT must still tread carefully, because the enterprise is permitting access by a device it doesn't own. A key challenge is to craft policies that provide adequate security assurance while at the same time respecting the owner's personal application and usage choices. After all, users who shell out hundreds of dollars for slick new tablets are going to install whatever applications they want.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

The tension between ownership and protection often boils over when IT tries to push policies that whitelist or blacklist apps in response to attackers unleashing malicious software that targets mobile platforms.

Dangerous Markets

This problem is particularly acute for Android, which has an enormous user base and a flexible app market. Tim Wyatt, principal security engineer at Lookout Mobile Security, says Android's open application distribution model allows apps to be pulled from multiple markets--including repackaged versions of legitimate apps. Malware is also on the Android Market itself. For example, according to Lookout's research, when DroidDreamLight emerged as a threat, it was found to be repackaged in 20 utility, nine porn, and five game apps in the Android Market. To make matters worse, the Android model relies on a user's ability to evaluate the permissions an app is requesting at install time.

Apple imposes stricter control over its own app market, but it's not a foolproof system. For instance, security researcher Charlie Miller developed a proof-of-concept malware app, called InstaStock, that made it into Apple's App Store--at least for a limited time.

So what's an IT policymaker to do? Risk-averse organizations will likely insist on tight policies that include app whitelisting and accept that they'll get pushback from users. Those with more liberal policies or that offer personal-device access to only nonsensitive data may elect to sidestep the issue, for now. Our advice: No matter your policy, use an app malware detection system, available from vendors such as McAfee, Symantec, and smaller players such as Lookout, that can be pushed as a mandatory installation via an MDM platform.

As with conventional antivirus packages for PCs, vendors for mobile platform AV must be able to demonstrate accurate detection and fast updates. If something is discovered, anti-malware systems should warn IT. Most MDM systems will allow you to quarantine an infected device until it's remediated.

Grant Moerschel is co-founder of WaveGard, a consulting firm. Write to us at iwletters@techweb.com.



Related Reading




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.