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Online and Mobile Device Identification: Is Your Online Authentication Security Strategy Ready to Go Mobile?
Javelin Strategy & Research, Oct 2010, Pages: 42
Device identification is a relatively inexpensive authentication process that provides a low to medium layer of protection with high ease of use for consumers. But is this online security strategy ready to go mobile? In this report, Javelin reviews the advantages and disadvantages of device identification and its ability to extend from online to mobile authentication. The need for better account authentication in financial services, retail, medical, social networks and gaming is urgent and growing. While mobile threats are still nascent, online attacks on nationwide financial institutions are increasing. At the same time, more consumers are purchasing smartphones and are also connecting to online and mobile sites through their mobile devices. Security vendors reviewed are Digital Resolve, 41st Parameter, Iovation, RSA and ThreatMetrix.
Primary Questions
- Why is there a need for a passive layer of security, such as device identification?
- What online authentication methods transfer to mobile authentication?
- What are the advantages and disadvantages of device identification?
- Will device identification work with mobile handsets?
- How does device identification help thwart criminal attacks and identify true customers?
- Which vendors supply digital identification? How are they differentiated?
Methodology
This report is based primarily on data collected online in August 2010 from 1,995 consumers representative of the U.S. population in gender, age, ethnicity and income. Overall margin of sampling error is ± 2.19 at the 95% confidence interval. The consumer data in this report also refers to data based on several surveys:
- This report is based primarily on data collected online in the United States from a random-sample panel of 3,100 respondents with mobile phones in July 2010; overall margin of sampling error is ±1.76 percentage points at the 95% confidence level.
- This report is also based on data collected online from a random-sample panel of 5,211 U.S. households in March 2010. The survey targeted respondents based on proportions of gender, age and income representative of those of the overall U.S. online population. Overall margin of sampling error is ±1.36% at the 95% confidence level.
- Data from a September 2009 telephone survey of 5,000 U.S. adults, including 703 identity fraud victims, was also used in this report. For questions answered by all 5,000 respondents, the maximum margin of sampling error is +/- 1.4% at the 95% confidence level. For questions answered by all 703 identity fraud victims, the maximum margin of sampling error is +/- 3.7% at the 95% confidence level. For questions answered by a proportion of all identity fraud victims, the maximum margin of sampling error varies and is greater than +/- 3.7% at the 95% confidence level.
- A random-sample panel of 3,000 consumers with mobile devices collected in July 2009, with an overall margin of sampling error of ±1.79 percentage points at the 95% confidence level.
It also incorporates the 2009 and 2010 Mobile Banking Scorecards, which reviewed the top 18 and 19 financial institutions, respectively, offering customer-facing mobile banking services (out of the top 40 and 30 financial institutions, respectively, by deposit base). The surveys targeted respondents based on proportions of gender, age, income and ethnicity representative of those of the overall U.S. online population. Rounding (in the underlying numbers) in charts accounts for the slight differences in percentages.
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