Lean On Me: Mining Internet Service Dependencies From Large-Scale DNS Data
作者： Matteo Dell'Amico , Leyla Bilge , Ashwin Kayyoor , Petros Efstathopoulos , Pierre-Antoine Vervier
关键词: Power graph analysis 、 The Internet 、 Computer science 、 Cascading failure 、 Data science 、 Dependency graph 、 Service provider 、 Service (business) 、 Cloud computing 、 Denial-of-service attack
摘要: Most websites, services, and applications have come to rely on Internet services (e.g., DNS, CDN, email, WWW, etc.) offered by third parties. Although employing such generally improves reliability cost-effectiveness, it also creates dependencies service providers, which may expose websites additional risks, as DDoS attacks or cascading failures. As cloud are becoming more popular, an increasing percentage of the overall ecosystem relies a decreasing number highly popular services. In our general effort assess security risk for given entity, motivated effects recent disruptions, we perform large-scale analysis passive active DNS datasets including than 2.5 trillion queries in order discover between this paper, present findings dataset analysis, attempt important insights about dependencies. To further understand nature dependencies, graph-theoretic dependency graph propose support power, novel power measure that can quantify amount dependence other particular service. Our reveal current is dominated handful providers---with Amazon being leader, far---whose popularity steadily increasing. These supported results, reveals set less-popular many (regional) depend on.
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