The Problem with Security Vendor Reports

The information security vendor space is flooded with research: annual reports, white papers, marketing publications — the list goes on and on. This research is subsequently handed to marketing folks (and engineers who are really marketers) where they fan out to security conferences across the world, standing in booths quoting statistics and attending pay-to-play speaking slots, convincing executives to buy their security products.

There’s a truth, however, that the security vendors know but most security practitioners and decision makers aren’t quite wise to yet. Much of the research vendors present in reports and marking brochures isn’t rooted in any defensible, scientific method. It’s an intentional appeal to fear, designed to create enough self-doubt to make you buy their solution.

This is how it’s being done:

  • Most vendor reports are based on surveys, also known as polls
  • Most of the surveys presented by security vendors ignore the science behind surveys, which is based on statistics and mathematics
  • Instead of using statistically significant survey methods, many reports use dubious approaches designed to lead the reader down a predetermined path

This isn’t exactly new. Advertisers have consumer manipulation down to an art form and have been doing it for decades. Security vendors, however, should be held to a higher standard due to fact that the whole field is based on trust and credibility. Many vendor reports are presented as security research and not advertisements.

What’s a survey?

A survey is a poll. Pollsters ask a small group of people a question, such as “In the last year, how many of your security incidents have been caused by insiders?” The results are extrapolated to apply it to a general population. For example, IBM conducted a survey that found that 59% of CISO’s experienced cyber incidents in which the attackers could defeat their defenses. The company that conducted the survey didn’t poll all CISO’s — they polled a sample of CISO’s and extrapolated a generality about the entire population of CISO’s.

This type of sampling and extrapolation is completely acceptable to do, if the survey adheres to established methodologies in survey science. Doing so makes the survey statistically significant; not doing it puts the validity of the results in question.

All surveys have some sort of error and bias. However, a good survey will attempt to control for this by doing the following:

  • Use established survey science methods to reduce the errors and bias
  • Disclose the errors and bias to the readers
  • Disclose the methodology used to conduce the survey
  • A good survey will also publish the raw data for peer review

Why you should care about statistically sound surveys

Surveys are everywhere in security. They are found in cute infographics, annual reports, journal articles and academic papers. Security professionals take these reports and read them, learn from them, quote them in steering committee meetings or to senior executives when they ask questions. Managers often ask security analysts to quantify risk with data — the easiest way is to find a related survey. We rely on the data to enable our firms to make risk-aware business decisions.

When you tell your Board of Directors that 43% of all data breaches are caused by internal actors, you’d better be right. The data you are using must be statistically significant and rooted in fact. If you are quoting vendor FUD or some marking brochure that’s disconnected from reality, your credibility is at stake. We are trusted advisors and everything we say must be defensible.

What makes a good survey

Everyone has seen a survey. Election and public opinion polls seem simple on the surface, but it’s very hard to do correctly. The science behind surveys are rooted in math and statistics; when the survey is, it’s statistically significant.

There are four main components of a statistically significant survey:

Population
This is a critical first step. What is the group that is being studied? How big is the group? An example would be “CISO’s” or “Information Security decision makers.”

Sample size
The size of the group you are surveying. It’s usually not possible to study an entire population, so a sample is chosen. A good survey taker will do all they can to ensure the sample size is as representative as the general population as possible. More importantly, the sample size needs to be randomly selected.

Confidence interval
Also known as the margin of error; (e.g. +/-); larger the sample size, the lower the margin of error.

Unbiased Questions
The questions themselves are crafted by a neutral professional trained in survey science. Otherwise, it is very easy to craft biased questions that lead the responder to answer in a certain way.

What makes a bad survey?

A survey will lose credibility as it uses less and less of the above components. There are many ways a survey could be bad, but here are the biggest red flags:

  • No disclosure of polling methodology
  • No disclosure of the company that conducted the poll
  • The polling methodology is disclosed, but no effort was made to make it random or representative of the population (online polls have this problem)
  • Survey takers are compensated (people will say anything for money)
  • Margin of error not stated

Be Skeptical

Be skeptical of vendor claims. Check for yourself and read the fine print. When you stroll the vendor halls at RSA or Blackhat and a vendor makes some outrageous claim about an imminent threat, dig deeper. Ask hard questions. We can slowly turn the ship away from FUD and closer to fact and evidence-based research.

And if you’re a vendor — think about using reputable research firms to perform your surveys.