Malware Insights: Android Infection Rates and Techniques for Identifying Unknown Malware

In the second research result of the month, we report on the recent results in understanding mobile malware. The research was presented and published in the prestigious World Wide Web conference in April 2014.

Research result of the month: Malware Insights - Android Infection Rates and Techniques for Identifying Unknown Malware

In the second research result of the month we report on the recent results in understanding mobile malware. Smartphones are now ubiquitous, personal and store a lot of personal information about their users. Calls and messaging cost money to users, and smartphones are also increasingly used for direct financial transactions. Therefore, one of the great fears about smartphone use is the possibility of large-scale viral infection.

The Malware Insights team at the Intel Collaborative Research Institute for Secure Computing (ICRI-SC) (http://www.icri-sc.org) at the Department have shown that infection rates in Android devices are around 0.25 per cent, significantly higher than the previous independent estimate. They also developed a technique to identify devices infected with previously unknown malware.

The project team, consisting of Hien Truong, Eemil Lagerspetz, Sourav Bhattacharya, and Petteri Nurmi working under the guidance of Professor N. Asokan and Professor Sasu Tarkoma, and collaborating with Adam J. Oliner from the UC Berkeley AMP Lab, published an article on the recent results at this year’s World Wide Web conference (http://www2014.kr/).

Android Infection Rates

There is a steady stream of news stories and announcements about how many more new strains of Android malware appear every passing year. Data showing infection rates in the real world has been hard to come by. There is a lot of data about the number of different malware samples discovered but not so much about the extent they are actually found in the wild. If smartphones were infected to the same extent as personal computers used to be, the resulting damage would be much more severe.

The few estimates that are out there vary greatly: ranging from more than 4 per cent of Android devices, according to an estimate by an anti-virus company, to less than 0.0009 per cent of smartphones in the US, according to a different estimate by group of academic researchers from the US.

What is the reason for this disparity?

The team has been investigating the true extent of malware infection in Android devices. They discovered that infection rates in Android devices are at around 0.25 per cent, significantly higher than the previous independent estimate. The project collected anonymized data from over 50 000 devices during a seven-month period.

An arXiv research report based on the work being done at the "Malware Insights" project at the department of Computer Science has been featured (http://www.technologyreview.com/view/522771/first-direct-measurement-of-infection-rates-for-smartphone-viruses/) in MIT Technology Review's "Emerging Technology From the arXiv" section.

Identifying Unknown Malware

"This is only the beginning. We are now trying to improve the accuracy of our results and are investigating whether we can identify vulnerable devices even before they are infected. I am very excited about the prospects of using data insights to improve security techniques,” professor Asokan explains.

The researchers speculated that smartphones infected with malicious apps may have other, benign, apps in common, possibly because the users purchase them all from the same app market. Based on this conjecture, the researchers investigated if it is possible to develop a technique to identify devices infected with previously unknown malware. In their dataset, this approach is up to five times more likely to identify infected devices than by choosing devices at random.

“The detection of zero-day malware applications is crucial for enabling the mitigation of their adverse effects. Our work aims to detect vulnerable devices and screen them so that new malware applications can be stopped as fast as possible,” professor Tarkoma adds.

Picture: From the left, Sourav Bhattacharya, Eemil Lagerspetz, Hien Truong and Adam J. Oliner attending the conference.

Link to the article:

The company you keep: mobile malware infection rates and inexpensive risk indicators. WWW 2014. http://doi.acm.org/10.1145/2566486.2568046.

Created date

24.04.2014 - 16:47

The university’s team Game of Nolife won Western European programming contest for students

In the finals in Thailand in spring 2016, the students from the University of Helsinki will face the best teams in the world.

The University of Helsinki has won the inter-university NWERC 2015 programming contest that was held in Linköping recently. It was attended by 95 teams from Western Europe. The Game of Nolife team from the University of Helsinki consisted of computer-science and maths students Tuukka Korhonen, Olli Hirviniemi and Otte Heinävaara.

The Carat research team has published a dataset focusing on collaborative energy diagnostics of mobile devices and applications

 

 

The Carat research team from University of Helsinki publishes a dataset from the Carat project (http://carat.cs.helsinki.fi/) focusing on collaborative energy diagnostics of mobile devices and applications. The dataset was presented at the IEEE PerCom’15 conference last spring in the publication "Energy Modeling of System Settings: A Crowdsourced Approach" that won the Marc Weiser Best Paper Award given at the conference.

Eemil Lagerspetz was awarded a grant by the Jorma Ollila fund of Nokia Foundation on November 24, 2015

 

 
 
Eemil Lagerspetz was awarded a grant by the Jorma Ollila fund of Nokia Foundation on November 24, 2015. Congratulations!
 
The fund was launched in year 2014 to support post doctoral research career development. 
The title of Eemil’s post doctoral research is “Mind The Gap: Combining Trajectory Datasets for a Holistic Picture of Human Mobility” and the research will be carried out at the Hong Kong University of Science and Technology (HKUST) in 2016.
 

Collaborative Networking (CoNe) group researchers got the best paper award at 2nd ACM Conference on Information-Centric Networking (ICN 2015)

 

Collaborative Networking (CoNe) group researchers got the best paper award at 2nd ACM Conference on Information-Centric Networking (ICN 2015), one of the most prestigious venues for ICN research. The article entitled Pro-Diluvian: Understanding Scoped-Flooding for Content Discovery in ICN is lead by Liang Wang - a recent PhD graduate from CoNe research group, and is the outcome of collaboration with Suzan Bayhan and Jussi Kangasharju from UH, Jörg Ott from Aalto University, Arjuna Sathiaseelan and Jon Crowcroft from Cambridge University.