Inferring Internet Denial-of-Service Activity Authors: David Moore, Geoffrey M. Voelker and Stefan Savage; University of California, San Diego Publish:

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Presentation transcript:

Inferring Internet Denial-of-Service Activity Authors: David Moore, Geoffrey M. Voelker and Stefan Savage; University of California, San Diego Publish: Usenix Security Symposium 2001 Presenter: Xingbo Gao

Outline Contribution Motivation Introduction of Denial-of-Service (DoS) Attacks Basic Methodology Attack Classification Results Strengths, Weakness and Improvements

Contribution Presented a novel technique “backscatter analysis” to estimate the worldwide DoS activity Performed three-week long real experiments on /8 network and classified the DoS attacks quantitatively

Motivation How prevalent are DoS attacks in the Internet today?  How often?  What attack protocols used?  Attack rate?  Attack duration?  Victim names and domains?  And more …

DoS Attack Introduction Devastating  Feb “fast” and “intense” assault took down Yahoo, Ebay and E*trade  Yahoo main site were unreachable for around three hours on Monday  "This was so fast and so intense that we couldn't even redirect our traffic," Yahoo spokesperson said. (CNN)  Jan manual mis-configuration of a router caused Microsoft websites unreachable for Tue and Wed; inaccessible throughout Thursday due to a DoS attack (PC World)  FBI investigated both incidents …

DoS Attack Introduction - contd Logic attacks: software flaws  Ping-of-Death Flooding attacks: overwhelm CPU, memory or network resources  SYN flood  TCP ACK, NUL, RST and DATA floods  ICMP Echo Request floods  And so on …

DoS Attack Introduction - contd SYN flood TCP RST SD SYN x SYN y, ACK x+1 ACK y+1 LISTEN SYN_RECVD CONNECTED AD Non-existent spoofed SYN LISTEN SYN_RECVD SYN+ACK Port flooding occurs

DoS Attack Introduction - contd Distributed denial-of-service attack (DDoS)  Control a group of “zombie” hosts to launch assault on specific target(s)  A botnet can perform the DDoS attacks IP spoofing  Attackers forge IP source addresses  Simple technique but very difficult to trace-back  “Backscatter” is based on IP spoofing

Basic Methodology - Backscatter AttackerVictim E B D backscatter

Experimental Platform Internet Hub /8 network Monitor n - # distinct IP addresses monitored m - # attacking packets R’ – measured average inter-arrival rate of backscatter

Attack Classification Flow-based classification  A flow is a series of consecutive packets sharing the same target IP address and IP protocol  Flow lifetime: fixed five-minute approach  Reduce noise and misconfiguration traffic by setting thresholds  Extract packet information from flows Event-based classification  Flow-based obscures time-domain characteristics  An attack event is defined by a victim emitting at least ten backscatter packets in one minute

Experimental Results Breakdown of attack protocols

Attack Frequency Estimated number of attacks per hour as a function of time (UTC)

Attack Rate and Duration Cumulative distribution of estimated attack rates in packets per second Probability density of attack durations

Strengths of the Paper Presented a novel technique “backscatter analysis” to estimate the worldwide DoS activity Performed three-week long real experiments on /8 network and classified the DoS attacks quantitatively Data is still available for public research

Weakness of the Paper Analysis Limitations  Uniformity of spoofed source addresses  Reliable delivery of backscatter  Backscatter hypothesis Difficult to validate Unable to explain some scenarios presented in resulted graphs

How to Improve the Paper? Find and create a theoretic model to model DoS attacks like worm propagation? Take geography into consideration Take more researches and experiments to fully explain the figures presented

Questions ?