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Using Economics to Quantify the Security of the Internet

Using Economics to Quantify the Security of the Internet. Jason Franklin. Internet Security (Availability). Claim 1: The security of the Internet is directly proportional to the number of compromised end-hosts

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Using Economics to Quantify the Security of the Internet

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  1. Using Economics to Quantify the Security of the Internet Jason Franklin

  2. Internet Security (Availability) • Claim 1: The security of the Internet is directly proportional to the number of compromised end-hosts • As the total number of compromised machines grows, the potential for larger DDoS attacks grows • More compromised machines implies more resources available to attackers • Security of the Internet is directly tied to the security of end-hosts in aggregate

  3. Internet Security (Availability) • Claim 2: Given a sufficiently powerful adversary, any networked resource can be DoSed successfully • Defenders are fundamentally more resource constrained than attackers • Defenders are restricted to play/pay by the rules • Over-provisioning and DoS defenses cost money

  4. Measuring Internet Security • Two basic research questions: • (Number): How many of the Internet’s end-hosts are compromised at any one time? • 100 million, 200 million, more? • (Cost): What is the effort required to compromise the security (availability) of a networked resource? • A security metric for Internet availability • Prefer quantity directly related to how much work or effort need be spent

  5. Estimating Number of Compromised End-hosts • Approach 1 (Scanning): • Scan entire IP address space with vulnerability scanner • Pros: • Would give reasonable estimate of number of hosts with well-known easy-to-exploit vulnerabilities • Cons: • Scanning won’t reach Internet’s edge (NATs etc.) • Vulnerability scanning is slow and noisy • Hosts that are compromised then patched would be missed

  6. Estimating Number of Compromised End-host • Approach 2 (Economics): • Establish market for compromised hosts • Monitor supply and demand • Pros: • Inexpensive to monitor market • Learn more than just quantity supplied • Cons: • Difficult to establish public market for stolen goods • Hard to entice buyers and sellers to participate

  7. Hard, but not impossible • Introducing #ccpower • Active underground market for cyber contraband • Includes buyers and sellers specializing in spam, phishing, scamming, hacking, credit card fraud, and identity theft • Global market with thousands of active buyers and sellers • Responsible for ~$100 million in credit card fraud each year, numerous phishing scams, and hordes of other illegal activity

  8. S erver Key C lient Collecting Economic Data C • Passive monitoring and archival of Internet Relay Chat (IRC) channels • 50+ monitored servers • Over 7 months of data • Over 12 million individual messages from as many as 50k individuals • Limitations and Complexities • No private IRC messages • Complex underground dialect (slang) • Difficult to establish reputation S IRC S C S C C C

  9. Market at a Glance Percentage of Monitored Messages Number of Days Monitored

  10. Identifying Useful Data • Text classification problem: • Given 13+ million IRC messages • Including millions of useful messages • “I’ve got hacked hosts for $2, pm me for deal” • And millions of useless messages • “Screw you guys I’m out of here” • Built binary text classifiers to identify interesting classes of data • Hacked hosts sale ads • Hacked hosts want ads • Phishing and spam related ads • Used SVMs with 3k line train set and 1k line test set • Bag of words feature vectors with TFIDF feature representation • SVMs correctly recall over 85% of true positives with precision of around 50% • For each true positive, SVMs identify one false positive

  11. Law of Demand All other factors being equal, the higher the price of a good, the smaller is the quantity demanded Law of Supply All other factors being equal, the higher the price of a good, the greater is the quantity supplied Economic Measurements

  12. Price of Hacked Hosts over Time Price Time Period (Days)

  13. $10 $10 # Compromised End-hosts • Methodology: • Market equilibrium price for compromised hosts at time t=1 is $10 • Market equilibrium price for compromised hosts at time t=2 is $5 • More compromised hosts are available at a lower price • But how do we know that supply shifted rather than demand? ? $5 ?

  14. Ceteris Paribus Assumption • Laws of Supply and Demand only hold under ceteris paribus assumption • “All other factors being equal” • Law of Demand’s Other Factors • Size of market (population) • Measurements show this is fixed • Consumer preferences • Income • Price of related goods • Law of Supply’s Other Factors • Cost of required resources (inputs) • Search cost for time spent searching for vulnerable hosts • Cost of exploits (free) • Technology • Scripts and tools mainly • Price of substitute and complement • Bulletproof hosting services for spammers • Substitutes for bots? Population Days

  15. Cost to Buy as a Security Metric • Each networked server S has fixed amount of available resources R • S has sufficient resources to service k hosts at per time period • In our simple model, S is vulnerable to a complete DoS attack by >= k hosts • Natural question to ask is “How much effort is required of an attacker to compromise k hosts?” • Before markets, effort required was dependent on skills of attacker and level of tools available • After markets, effort required at time t can be measured by the Cost to Buy k hosts at time t

  16. Cost to Buy Metric • A simple example: • Server S has sufficient resources to service 30 hosts per time period • Security w.r.t. an adversary: • S is 20 (50-30) under provisioned against a $100 adversary at time t • S is 5 over provisioned against a $100 adversary at time t+1 • Independent of adversary: • S is $60 (30 * $2) secure at time t and $120 (30 * $4) secure at time t+1 • Measures resources required by adversary / measures risk

  17. Conclusion • We looked at how economics can be used to quantify the security of the Internet in a natural way • Asked how many of Internet end-hosts are compromised • Established trend suggesting that the number of compromised hosts is increasing rather than decreasing • Developed the cost to buy security metric to quantity resources of adversary necessary to effect the available of a resource • Price provides natural way to quantify resources

  18. Remaining Work • Use simultaneous equation models from econometrics to empirically estimate supply and demand curves • Allows for estimate of quantity supplied at a price • Use event study methodology to correlate Internet security “events” with the price of compromised hosts • New form of validation for security metrics

  19. Questions? • Acknowledgements: • Paul Bennett,John Bethencourt, Gaurav Kataria, Leonid Kontorovich, Pratyusa K. Manadhata, Vern Paxson, Adrian Perrig, Srini Seshan, Stefan Savage

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