An Economic Approach to Info Security


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Ed Bellis Keynote at IANS Twin Cities Security Forum.

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  • From Shaman to Scientist - A Use Case in Data Driven Security\n
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  • Talk about WEIS. Security is an opaque attribute within the software market. It is not easily apparent to the buyer how much security they are getting when they purchase software. This is similar to quality within the automotive industry. There are no good ways to determine what you are getting. This is a problem for the buyer and we need to figure out how to make security more transparent to the software purchaser. \n
  • Developers are rarely incented by software security. Speed to market, functionality and other code quality factors are often prioritized over secure code. Revenues and customer acquisition is rarely driven by security. This creates a lack of incentives around software security.\n
  • Security is a negative externality. This is creates very big issues in the broader security of systems and the internet. A commonly used example in security of a negative externality are botnets. As an avg user on the internet I have very little incentive to secure my machine from being part of a botnet. Other than some bandwidth or system resource consumption, it doesn’t do me much harm. But those suffering a DDOS attack via a botnet are suffering the consequence from the avg user not protecting their machine. In other words, those with the power to protect are not incented to do so.\n
  • proving the negative is hard. why not just sell on emotion? talk about secrecy of controls - no sharing of data except bad guys - follow best practices lest you be hacked. Use the data proves negligence example. Lawyers suck at risk mgmt.\n
  • We need to take a more data driven approach to security. Relying on metrics and yes and in some cases real live outcomes and evidence. There are a lot of complaints in our field about a lack of information, and while I don’t disagree often times we are not even using the information that we have! I’m going to walk through a few use cases. These are all baby steps to get to where we eventually need to be but we gotta start somewhere. Using less secrecy & religion and more openness and information sharing. In order to take the first steps, we have to get our own house in order.\n
  • simple example of using what we have. sprinkle in some metadata!\n
  • Metasploit has become table stakes. \n
  • A lot of different attributes could go into determining the “why”. Is a particular team less responsive to patching and updates? Is it the technology stack that is more prone to vulnerability or misconfiguration? Are there other environmental reasons? By determining root cause you may more accurately predict the next issue as well as risk rank new projects or applications prior to deployment. By combining vulnerability, misconfig, defect and issue data with operational data such as log and events, threat feeds, and breach data (need more of this), we could also take our predictive analytics to security breaches not just issues.\n\n
  • making more meaningful priority decisions - credit: Jeff Lowder CVSS ignores information about the base rates of vulnerability exploitation.\nI have an older version of Apache that if I were to upgrade to the current version would eliminate 14 vulnerabilities. I also have an older version of Tomcat that if I were to upgrade to the current version would eliminate 9 vulnerabilities. If CVSS included a base rate on these reference classes, this would help me prioritize my remediation resources more appropriately.\n
  • A study by Thomas Zimmerman of MS and Stephan Neuhaus mines the CVE database looking at all sorts of trends. It’s a good paper. There’s a table near the end that clearly shows the increase in vulnerabilities through the application layer with a decrease of many of the more traditional network vulnerabilities over time. Yet we continue to prioritize our spending and resources on the attacks of 5+ years ago.\n
  • Insert Alex Hutton formula\n4:14:40 PM Alex Hutton: once the data hits catwalk we decision and the threat is funneled off....\n4:15:46 PM Ed Bellis: haha its a new risk language\n4:16:05 PM Ed Bellis: you guys pull a lot of public sources of data?\n4:16:16 PM Alex Hutton: not yet\n4:16:21 PM Alex Hutton: some but not a ton\n4:16:24 PM Ed Bellis: also any insight on whether VERIS taking off?\n4:16:41 PM Alex Hutton: there's a broader vision (you can fit) that would make a lot of sense\n4:17:02 PM Alex Hutton: but that would take cooperation from various sources which is going to be hard, and why VERIS is a bit stalled\n4:17:17 PM Alex Hutton: there are lots of folks using VERIS, but not sharing data\n4:17:31 PM Ed Bellis:\n4:17:51 PM Ed Bellis: i'd love to tap into that\n4:19:34 PM Alex Hutton: well, the better vision is for you to feed data along with threat (and incident data) into decision making on a daily or even hourly basis\n4:19:50 PM Alex Hutton: In a sense, you hold not only the orgs perimeter, but a broad sample of perimeters\n4:20:04 PM Alex Hutton: and their\n4:20:12 PM Alex Hutton: vuln posture\n4:20:38 PM Alex Hutton: So\n4:21:07 PM Ed Bellis: right we want to move into a position where our data becomes the primary asset to help make better security decisions\n4:21:16 PM Ed Bellis: *not a verb*\n4:21:49 PM Alex Hutton: My(vuln posture * other threat activity) / (other vuln posture * other threat activity) = a much better metric than just vuln data\n4:22:24 PM Ed Bellis: meaning am i safer than my neighbor?\n4:22:25 PM Alex Hutton: in fact, a very interesting likelihood data point to do some degree of probabilistic analysis on that I don't have the time to really explore yet, but is very, very interesting\n4:23:10 PM Alex Hutton: that may be a byproduct, more about establishing a rate at which I can expect my luck to run out.\n4:23:23 PM Ed Bellis: i see\n4:23:35 PM Alex Hutton: so you're the CSO of Orbitz, you know you have a vuln. to specific threat activity.  So far, you're lucky\n4:24:02 PM Alex Hutton: but what about establishing rate of threat activity vs. how pervasive that same vuln is around other orgs?\n4:24:31 PM Ed Bellis: where do we get the rate of threat activity?\n4:24:42 PM Ed Bellis: breach db's?\n4:24:51 PM Alex Hutton: High Threat Activity + Low pervasiveness in the aggregate population = Luck running out.\n4:25:06 PM Alex Hutton: nope.  that's part of your exit strategy\n4:25:19 PM Ed Bellis: bought by verizon ?\n4:25:33 PM Alex Hutton: Some MSSP who is running or aggregating WAF data, Firewall/IDS/IPS data\n4:25:58 PM Alex Hutton: you as "Yet another managed service" well, that's a scenario I believe in, yes.\n4:26:20 PM Alex Hutton: But you as "Next generation in managed services by data aggregation" is going to be very, very compelling, I think\n4:26:46 PM Alex Hutton: what you have to understand (and I think you do) is how to leverage your data into "decision" (the verb)\n
  • talk about infosec vs fraud\n
  • This is a great TED talk about the medical industry. Talking about how we have created a system where we believe there are doctors who make mistakes and ones who dont. It’s a fallacy driven by ideology & lawyers. Our industry is very much like this. We NEED to talk about our mistakes. Talk about founding a startup and the founders who share their failure stories and WHY. Talk about fraud mgmt and how they do the same. Security NEEDS to. We need to share more about our failures and what lead to those outcomes. This can raise the bar of the entire industry and it’s completely silly to think their are orgs out there not making security mistakes. security is NOT binary, there are many shades of gray, The most common question “are we secure?”.\n
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  • An Economic Approach to Info Security

    1. 1. An Economic Approach to InfoSec
    2. 2. Nice To Meet YouAbout Me CoFounder HoneyApps Former CISO Orbitz Contributing Author Beautiful Security CSO Magazine/Online Writer InfoSec Island BloggerAbout Risk I/O Data-Driven Vulnerability Management as a Service 16 Hot Startups - eWeek 3 Startups to Watch - Information Week
    3. 3. Security is a Lemons Market
    4. 4. Lacks Incentives
    5. 5. Negative Externalities
    6. 6. An Industry Built on FUD
    7. 7. A Data DrivenApproach
    8. 8. Example Use Case 1 DLP CMDB Vuln SIEM Mgmt
    9. 9. Example Use Case 2 HD Moore’s Law - Josh Corman aka Security Mendoza Line “Compute power grows at the rate of doubling about every 2 years” “Casual attacker power grows at the rate of Metasploit”
    10. 10. Example Use Case 3Predicting Vulnerability (or even breach) Trending Key Attributes Outcomes
    11. 11. Example Use Case 4CVSS &The Base credit:Rate Fallacy Jeff Lowder
    12. 12. Example Use Case 5CVE Trending Analysis Gunnar’s Debt Clock
    13. 13. Example Use Case 6 Targets of Opportunity?My(vuln posture X other threat activity) / (other vuln posture X other threat activity)
    14. 14. (we need more of this)
    15. 15. talking about our mistakes
    16. 16. Q&Afollow us the blog twitter @ebellis And one more thing.... @risk_io We’re Hiring!