Gal Badishi, Idit Keidar, Amir Sasson

1. Exposing and Eliminating Vulnerabilities to Denial of Service Attacks in SecureGossip-Based Multicast Gal Badishi, Idit Keidar, Amir Sasson Faculty of Electrical Engineering, Technion

2. Agenda • Overview of gossip-based multicast • The problem • Proposed solution • Analysis and simulations • Implementation and measurements • Conclusions Faculty of Electrical Engineering, Technion

3. Multicast • A group of members • At least one member is a source – generates messages • Messages should arrive to all of the group members in a timely fashion • Network level vs. application level (ALM) Faculty of Electrical Engineering, Technion

4. Source Tree-Based Multicast • Use a spanning tree – most common solution • No duplicates (optimal BW when network-level) • Single points of failure Faculty of Electrical Engineering, Technion

5. Gossip-Based Multicast • Progresses in rounds • Every round • Choose random partners (view ) • Send or receive messages • Discard old msgs from buffer • Probabilistic reliability • Trades latency and BW for redundancy • Two methods • Push • Pull Faculty of Electrical Engineering, Technion

6. Push Source Faculty of Electrical Engineering, Technion

7. Pull Source Faculty of Electrical Engineering, Technion

8. Hostility over the Internet • Forgery/spoofing • Penetration • Denial of Service (DoS) Faculty of Electrical Engineering, Technion

9. Denial of Service • Unavailability of service • Methods • Exploiting bugs • Exhausting resources • Remote attacks • Network level • Application level • Got little attention • No quantitative analysis of impact on application Faculty of Electrical Engineering, Technion

10. Dollar Amount of Losses by Type Faculty of Electrical Engineering, Technion

11. Valid Request Bogus Request Remote Application-Level DoS No Attack DoS Attack Faculty of Electrical Engineering, Technion

12. Effects of DoS on Gossip • Reasonable to assume that source is attacked • Surprisingly, we show that naïve gossip is vulnerable to DoS attacks • Attacking a process in pull-based gossip may prevent it from sending messages • Attacking a process in push-based gossip may prevent it from receiving messages Faculty of Electrical Engineering, Technion

13. Our Solution • Drum – a new gossip-based ALM protocol • Utilizes DoS-mitigation techniques • Separating and bounding resources • Combining both push and pull • Using random one-time ports to communicate • Proven robust using formal analysis and quantitative evaluation • Provides general methods for analyzing and quantitatively evaluating resistance to DoS-attacks Faculty of Electrical Engineering, Technion

14. Round Duration Valid Request Bogus Request Bounding Resources • Motivation: prevent resource exhaustion • Each round process a random subset of the arriving messages and discard the rest Faculty of Electrical Engineering, Technion

15. Combining Push and Pull • Attacking push cannot prevent receiving messages via pull (random ports) • Attacking pull cannot prevent sending via push Faculty of Electrical Engineering, Technion

16. Random Ports • Any request necessitating a reply contains a random port number • “Invisible” to the attacker (e.g., encrypted) • The reply is sent to that random port • Assumption: attacking other ports does not affect the random port’s queue (i.e., there is no BW exhaustion) Faculty of Electrical Engineering, Technion

17. Drum’s Push Mechanism • Alice sends Bob a push-offer • Bob replies with a digest of messages he has already received • Alice only sends Bob messages missing from his digest • Random ports Faculty of Electrical Engineering, Technion

18. Evaluation Methodology • Compare 3 protocols • Push (push-based with bounded resources) • Pull (pull-based with bounded resources) • Drum • Under various DoS attacks • Fixed strength • Increasing strength • Source is always attacked • Evaluates combination of Push and Pull Faculty of Electrical Engineering, Technion

19. Evaluation Methodology (cont.) • Measure propagation time – expected number of rounds it takes a message to reach all of the correct processes • 99% in the simulations and actual measurements • Use real implementation to measure actual latency and throughput Faculty of Electrical Engineering, Technion

20. Analysis/Simulation Assumptions • Static group with complete connectivity • Processes have complete group knowledge • Propagation of a single message M • But simulate situation where all procs have msgs to send • M is never purged from local buffers • Rounds are synchronized • All round operations complete within the same round • All processes are correct (analysis) or 10% of them perform a DoS attack (simulation) Faculty of Electrical Engineering, Technion

21. Validating Known Results • The propagation time of gossip-based multicast protocols is O(log n) [P87, KSSV00] Faculty of Electrical Engineering, Technion

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23. Validating Known Results (cont.) • The performance of gossip-based multicast protocols degrades gracefully as failures amount [LMM00, GvRB01] Faculty of Electrical Engineering, Technion

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25. Definitions • n – number of processes in the group • F – size of view, and max # of requests to process in a round (F = 4 ) •  – percentage of attacked processes • x – number of bogus messages an attacked process receives in a round • B – total attack strength (B = nx ) Faculty of Electrical Engineering, Technion

26. Analysis – Increasing Strength • Lemma 1: Fix  and n. Drum’s propagation time is bounded from above by a constant independent of x • Proof idea • Define effective fan-in and effective fan-out • Both have an element independent of x • When x   this element is dominant • The effective fans are bounded from below Faculty of Electrical Engineering, Technion

27. Analysis – Increasing Strength • Lemma 2: Fix  and n. The propagation time of Push grows at least linearly with x • Proof idea • Assume all non-attacked processes already have the message (and so does the source) • Bound the expected number of processes having M at round k from above • Find the minimal k in which all processes have M • Reaching all attacked processes takes at least a time linear in x Faculty of Electrical Engineering, Technion

28. Analysis – Increasing Strength • Lemma 3: Fix  and n. The propagation time of Pull grows at least linearly with x • Proof idea • Denote by p the probability that the source reads a valid pull request in a round • # of rounds for M to leave the source is geometrically distributed with p • The expectation is 1/p • 1/p is at least linear in x Faculty of Electrical Engineering, Technion

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31. Analysis – Fixed Strength • Define c = B/nF (total attack strength divided by total system capacity) • Lemma 4: For c > 5, Drum’s expected propagation time is monotonically increasing with  • Proof idea • Effective fan-in and effective fan-out are monotonically decreasing with  Faculty of Electrical Engineering, Technion

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33. Implementation and Measurements • Uses the Java programming language • Multithreaded processes • Operations are not synchronized • Rounds are not synchronized among processes • 50 machines on a 100Mbit LAN (Emulab) • One process per machine • 5 processes (10%) perform a DoS attack Faculty of Electrical Engineering, Technion

34. Validating the Simulations • Evaluate the protocols in the same scenarios tested by simulation • High correlation shows that the simplifying assumptions have little effect on the results Faculty of Electrical Engineering, Technion

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37. High-Throughput Experiments • Single source • Creates 40 messages (50 bytes long) per second • Total of 10,000 messages • Round duration = 1 second • Messages are purged after 10 rounds • Each process sends at most 80 data messages to another process in a round • Throughput and latency are measured at the 44 correct receiving processes Faculty of Electrical Engineering, Technion

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41. Conclusions • DoS attacks are a real problem • Gossip-based protocols have no single points of failure • However, naïve gossip-based protocols are vulnerable to targeted DoS attacks • Drum uses simple techniques to mitigate the effects of DoS attacks • Evaluations show Drum’s resistance to DoS • The most effective attack against Drum is a broad one • General DoS-mitigation techniques: random ports and neighbor-selection • Analysis and quantitative evaluation techniques may be applicable to other systems as well Faculty of Electrical Engineering, Technion

42. The End Faculty of Electrical Engineering, Technion