RSA Conference: Innovation in a Sea of Booths
- Date:April 15, 2019
- Author(s):
- Sean Sposito
- Kyle Marchini
- Report Details: 13 pages, 4 graphics
- Research Topic(s):
- Cybersecurity
- Fraud Management
- Fraud & Security
- PAID CONTENT
Overview
What started off as a conference meant to spotlight innovations in cryptography has become a swamp of sales-focused booths and occasionally outlandish presentations – exemplifying the chaos of an industry that continues to overwhelm security executives. As it does every year, Javelin engaged with vendors demonstrating on the expo floor, including managed security service providers; authentication vendors; and endpoint security companies, to name a few.
This report spotlights several new and innovative vendors based on a select set of criteria. The firms had to have marketed themselves to financial services clients; be considered an early-stage company (no more than B-Series funding); offer an approach that meets a new need in the market, or that tackles an old problem in a new way; present a compelling use case; and provide a detailed understanding of their technology. The profiled startups broke down into the following categories:
- Fraud and cybercrime attribution (4iQ)
- Automated attack protection (Arkose Labs)
- Threat intelligence (HYAS Infosec Inc.)
- Breach attack simulation (SCYTHE)
- Behavioral biometrics (UnifyID)
Methodology
Data in this report is taken from two surveys:
- A random-sample panel of 800 information technology security decision-makers, 200 of whom work in financial services, fielded in January 2018. For questions answered by all 800 survey respondents, the maximum margin of sampling error is ±3.46 percentage points at the 95% confidence level. For questions answered by all 200 financial services respondents, the maximum margin of sampling error is ±6.93 percentage points at the 95% confidence level. The margin of error is higher for questions answered by subsegments.
- A random sample panel of 5,000 U.S. adults fielded in November 2018. For questions answered by all 5,000 respondents, the maximum margin of sampling error is ±1.41 percentage points at the 95% confidence level.
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