Big Data. Big Decisions
InformationWeek
Special Coverage Series


Google's Android Malware Detection Falls Short

Google's app verification service, introduced in Android 4.2, catches only a fifth of malware samples at best, a recent study reports.

10 Best Business Tools In Google+
10 Best Business Tools In Google+
(click image for larger view and for slideshow)
Android appears to be on a trajectory to become the Windows of mobile operating systems, but there's a downside to ubiquity. Rising market share means increasing attention from malware authors.

Sophos, a computer security company, asserts that there is a growing malware problem for Android devices and that Android devices are less safe than iOS or Windows Phone devices. The FBI has noticed too, issuing a warning in October about risks facing Android users.

More Insights

Webcasts

More >>

White Papers

More >>

Reports

More >>

Google appears to be aware that Android needs better security. In September, it bought VirusTotal.com, a company that measures the effectiveness of malware detection engines. And Android 4.2 "Jelly Bean" includes a new app verification service to help identify potentially malicious apps.

[ Will Apple products be more secure if they are made in the United States? Read Apple Mac To Be Made In USA. ]

But a study published recently by Xuxian Jiang, associate professor of computer science at North Carolina State University, finds that Google's app verification service can identify only 15% to 20% of known Android malware.

The study also found that existing third-party security software for Android -- from Avast, AVG, TrendMicro, Symantec, BitDefender, ClamAV, F-Secure, Fortinet, Kaspersky and Kingsoft -- performed significantly better at detecting malware, with accuracy ranging from 51% to 100%.

In his study, Jiang says that the app verification service's reliance on SHA1 cryptographic hashes to identify malware files "is fragile and can be easily bypassed." Malware authors can simply repackage or alter their files to create different hash values, a fact that had forced the creators of computer security products to look beyond signature-based solutions.

Jiang suggests that Google's cloud-based approach to security could be augmented by more on-device security capabilities. In an email, he said the app verification service can be considered a move toward enhancing client-side security, but the "signature-based approach (adopted in most of current AV systems) can never keep up with the speed at which malware is created and evolved."

He recommends that Google look into collecting more information about apps, inasmuch as privacy considerations allow. He also says Google should "beef up the app verification service or integrate with more advanced server support," through integration with Bouncer, an app scanning mechanism that Google introduced in February, or Google's newly acquired VirusTotal.com.

Google didn't immediately respond to a request for comment.



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.