Faculty of Electrical Engineering, Technion May 2004 Gal Badishi Exposing and Eliminating Vulnerabilities to Denial of Service Attacks in Secure Gossip-Based Multicast Gal Badishi, Idit Keidar, Amir Sasson

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 AgendaAgenda Overview of gossip-based multicast Overview of gossip-based multicast The problem The problem Proposed solution Proposed solution Analysis and simulations Analysis and simulations Implementation and measurements Implementation and measurements Conclusions Conclusions Overview of gossip-based multicast Overview of gossip-based multicast The problem The problem Proposed solution Proposed solution Analysis and simulations Analysis and simulations Implementation and measurements Implementation and measurements Conclusions Conclusions

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 MulticastMulticast A group of members A group of members At least one member is a source – generates messages At least one member is a source – generates messages Messages should arrive to all of the group members in a timely fashion Messages should arrive to all of the group members in a timely fashion Network level vs. application level (ALM) Network level vs. application level (ALM) A group of members A group of members At least one member is a source – generates messages At least one member is a source – generates messages Messages should arrive to all of the group members in a timely fashion Messages should arrive to all of the group members in a timely fashion Network level vs. application level (ALM) Network level vs. application level (ALM)

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Tree-Based Multicast Use a spanning tree – most common solution Use a spanning tree – most common solution No duplicates (optimal BW when network-level) No duplicates (optimal BW when network-level) Single points of failure Single points of failure Use a spanning tree – most common solution Use a spanning tree – most common solution No duplicates (optimal BW when network-level) No duplicates (optimal BW when network-level) Single points of failure Single points of failure Source

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Gossip-Based Multicast Progresses in rounds Progresses in rounds Every round Every round –Choose random partners (view ) –Send or receive messages –Discard old msgs from buffer Probabilistic reliability Probabilistic reliability Trades latency and BW for redundancy Trades latency and BW for redundancy Two methods Two methods –Push –Pull Progresses in rounds Progresses in rounds Every round Every round –Choose random partners (view ) –Send or receive messages –Discard old msgs from buffer Probabilistic reliability Probabilistic reliability Trades latency and BW for redundancy Trades latency and BW for redundancy Two methods Two methods –Push –Pull

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 PushPush Source

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 PullPull Source

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Hostility over the Internet Forgery/spoofing Forgery/spoofing Penetration Penetration Denial of Service (DoS) Denial of Service (DoS) Forgery/spoofing Forgery/spoofing Penetration Penetration Denial of Service (DoS) Denial of Service (DoS)

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Denial of Service Unavailability of service Unavailability of service Methods Methods –Exploiting bugs –Exhausting resources Remote attacks Remote attacks –Network level –Application level Got little attention Got little attention No quantitative analysis of impact on application No quantitative analysis of impact on application Unavailability of service Unavailability of service Methods Methods –Exploiting bugs –Exhausting resources Remote attacks Remote attacks –Network level –Application level Got little attention Got little attention No quantitative analysis of impact on application No quantitative analysis of impact on application

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Dollar Amount of Losses by Type

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Remote Application-Level DoS Valid Request Bogus Request No Attack DoS Attack

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Effects of DoS on Gossip Reasonable to assume that source is attacked Reasonable to assume that source is attacked Surprisingly, we show that naïve gossip is vulnerable to DoS attacks 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 pull-based gossip may prevent it from sending messages Attacking a process in push-based gossip may prevent it from receiving messages Attacking a process in push-based gossip may prevent it from receiving messages Reasonable to assume that source is attacked Reasonable to assume that source is attacked Surprisingly, we show that naïve gossip is vulnerable to DoS attacks 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 pull-based gossip may prevent it from sending messages Attacking a process in push-based gossip may prevent it from receiving messages Attacking a process in push-based gossip may prevent it from receiving messages

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Our Solution Drum – a new gossip-based ALM protocol Drum – a new gossip-based ALM protocol Utilizes DoS-mitigation techniques 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 Proven robust using formal analysis and quantitative evaluation –Provides general methods for analyzing and quantitatively evaluating resistance to DoS-attacks Drum – a new gossip-based ALM protocol Drum – a new gossip-based ALM protocol Utilizes DoS-mitigation techniques 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 Proven robust using formal analysis and quantitative evaluation –Provides general methods for analyzing and quantitatively evaluating resistance to DoS-attacks

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Bounding Resources Motivation: prevent resource exhaustion Motivation: prevent resource exhaustion Each round process a random subset of the arriving messages and discard the rest Each round process a random subset of the arriving messages and discard the rest Motivation: prevent resource exhaustion Motivation: prevent resource exhaustion Each round process a random subset of the arriving messages and discard the rest Each round process a random subset of the arriving messages and discard the rest Valid Request Bogus Request Round Duration

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Combining Push and Pull Attacking push cannot prevent receiving messages via pull (random ports) Attacking push cannot prevent receiving messages via pull (random ports) Attacking pull cannot prevent sending via push Attacking pull cannot prevent sending via push Attacking push cannot prevent receiving messages via pull (random ports) Attacking push cannot prevent receiving messages via pull (random ports) Attacking pull cannot prevent sending via push Attacking pull cannot prevent sending via push

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Random Ports Any request necessitating a reply contains a random port number 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 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) Assumption: attacking other ports does not affect the random port’s queue (i.e., there is no BW exhaustion) Any request necessitating a reply contains a random port number 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 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) Assumption: attacking other ports does not affect the random port’s queue (i.e., there is no BW exhaustion)

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Drum’s Push Mechanism Alice sends Bob a push-offer Alice sends Bob a push-offer Bob replies with a digest of messages he has already received Bob replies with a digest of messages he has already received Alice only sends Bob messages missing from his digest Alice only sends Bob messages missing from his digest Random ports Random ports Alice sends Bob a push-offer Alice sends Bob a push-offer Bob replies with a digest of messages he has already received Bob replies with a digest of messages he has already received Alice only sends Bob messages missing from his digest Alice only sends Bob messages missing from his digest Random ports Random ports

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Evaluation Methodology Compare 3 protocols Compare 3 protocols –Push (push-based with bounded resources) –Pull (pull-based with bounded resources) –Drum Under various DoS attacks Under various DoS attacks –Fixed strength –Increasing strength Source is always attacked Source is always attacked Evaluates combination of Push and Pull Evaluates combination of Push and Pull Compare 3 protocols Compare 3 protocols –Push (push-based with bounded resources) –Pull (pull-based with bounded resources) –Drum Under various DoS attacks Under various DoS attacks –Fixed strength –Increasing strength Source is always attacked Source is always attacked Evaluates combination of Push and Pull Evaluates combination of Push and Pull

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Evaluation Methodology (cont.) Measure propagation time – expected number of rounds it takes a message to reach all of the correct processes 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 Use real implementation to measure actual latency and throughput Measure propagation time – expected number of rounds it takes a message to reach all of the correct processes 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 Use real implementation to measure actual latency and throughput

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Analysis/Simulation Assumptions Static group with complete connectivity Static group with complete connectivity Processes have complete group knowledge Processes have complete group knowledge Propagation of a single message M Propagation of a single message M –But simulate situation where all procs have msgs to send M is never purged from local buffers M is never purged from local buffers Rounds are synchronized Rounds are synchronized All round operations complete within the same round All round operations complete within the same round All processes are correct (analysis) or 10% of them perform a DoS attack (simulation) All processes are correct (analysis) or 10% of them perform a DoS attack (simulation) Static group with complete connectivity Static group with complete connectivity Processes have complete group knowledge Processes have complete group knowledge Propagation of a single message M Propagation of a single message M –But simulate situation where all procs have msgs to send M is never purged from local buffers M is never purged from local buffers Rounds are synchronized Rounds are synchronized All round operations complete within the same round All round operations complete within the same round All processes are correct (analysis) or 10% of them perform a DoS attack (simulation) All processes are correct (analysis) or 10% of them perform a DoS attack (simulation)

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Validating Known Results The propagation time of gossip-based multicast protocols is O(log n) [P87, KSSV00] The propagation time of gossip-based multicast protocols is O(log n) [P87, KSSV00]

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Validating Known Results (cont.) The performance of gossip-based multicast protocols degrades gracefully as failures amount [LMM00, GvRB01] The performance of gossip-based multicast protocols degrades gracefully as failures amount [LMM00, GvRB01]

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 DefinitionsDefinitions n – number of processes in the group n – number of processes in the group F – size of view, and max # of requests to process in a round (F = 4 ) F – size of view, and max # of requests to process in a round (F = 4 )  – percentage of attacked processes  – percentage of attacked processes x – number of bogus messages an attacked process receives in a round x – number of bogus messages an attacked process receives in a round B – total attack strength (B =  nx ) B – total attack strength (B =  nx ) n – number of processes in the group n – number of processes in the group F – size of view, and max # of requests to process in a round (F = 4 ) F – size of view, and max # of requests to process in a round (F = 4 )  – percentage of attacked processes  – percentage of attacked processes x – number of bogus messages an attacked process receives in a round x – number of bogus messages an attacked process receives in a round B – total attack strength (B =  nx ) B – total attack strength (B =  nx )

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Analysis – Increasing Strength Lemma 1: Fix  and n. Drum’s propagation time is bounded from above by a constant independent of x Lemma 1: Fix  and n. Drum’s propagation time is bounded from above by a constant independent of x Proof idea 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 Lemma 1: Fix  and n. Drum’s propagation time is bounded from above by a constant independent of x Lemma 1: Fix  and n. Drum’s propagation time is bounded from above by a constant independent of x Proof idea 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

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Analysis – Increasing Strength Lemma 2: Fix  and n. The propagation time of Push grows at least linearly with x Lemma 2: Fix  and n. The propagation time of Push grows at least linearly with x Proof idea 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 Lemma 2: Fix  and n. The propagation time of Push grows at least linearly with x Lemma 2: Fix  and n. The propagation time of Push grows at least linearly with x Proof idea 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

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Analysis – Increasing Strength Lemma 3: Fix  and n. The propagation time of Pull grows at least linearly with x Lemma 3: Fix  and n. The propagation time of Pull grows at least linearly with x Proof idea 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 Lemma 3: Fix  and n. The propagation time of Pull grows at least linearly with x Lemma 3: Fix  and n. The propagation time of Pull grows at least linearly with x Proof idea 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

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Analysis – Fixed Strength Define c = B/nF (total attack strength divided by total system capacity) 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  Lemma 4: For c > 5, Drum’s expected propagation time is monotonically increasing with  Proof idea Proof idea –Effective fan-in and effective fan-out are monotonically decreasing with  Define c = B/nF (total attack strength divided by total system capacity) 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  Lemma 4: For c > 5, Drum’s expected propagation time is monotonically increasing with  Proof idea Proof idea –Effective fan-in and effective fan-out are monotonically decreasing with 

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Implementation and Measurements Uses the Java programming language Uses the Java programming language Multithreaded processes Multithreaded processes Operations are not synchronized Operations are not synchronized Rounds are not synchronized among processes Rounds are not synchronized among processes 50 machines on a 100Mbit LAN (Emulab) 50 machines on a 100Mbit LAN (Emulab) One process per machine One process per machine 5 processes (10%) perform a DoS attack 5 processes (10%) perform a DoS attack Uses the Java programming language Uses the Java programming language Multithreaded processes Multithreaded processes Operations are not synchronized Operations are not synchronized Rounds are not synchronized among processes Rounds are not synchronized among processes 50 machines on a 100Mbit LAN (Emulab) 50 machines on a 100Mbit LAN (Emulab) One process per machine One process per machine 5 processes (10%) perform a DoS attack 5 processes (10%) perform a DoS attack

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 Validating the Simulations Evaluate the protocols in the same scenarios tested by simulation Evaluate the protocols in the same scenarios tested by simulation High correlation shows that the simplifying assumptions have little effect on the results High correlation shows that the simplifying assumptions have little effect on the results Evaluate the protocols in the same scenarios tested by simulation Evaluate the protocols in the same scenarios tested by simulation High correlation shows that the simplifying assumptions have little effect on the results High correlation shows that the simplifying assumptions have little effect on the results

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 High-Throughput Experiments Single source Single source Creates 40 messages (50 bytes long) per second Creates 40 messages (50 bytes long) per second Total of 10,000 messages Total of 10,000 messages Round duration = 1 second Round duration = 1 second Messages are purged after 10 rounds Messages are purged after 10 rounds Each process sends at most 80 data messages to another process in a round 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 Throughput and latency are measured at the 44 correct receiving processes Single source Single source Creates 40 messages (50 bytes long) per second Creates 40 messages (50 bytes long) per second Total of 10,000 messages Total of 10,000 messages Round duration = 1 second Round duration = 1 second Messages are purged after 10 rounds Messages are purged after 10 rounds Each process sends at most 80 data messages to another process in a round 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 Throughput and latency are measured at the 44 correct receiving processes

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004 ConclusionsConclusions DoS attacks are a real problem DoS attacks are a real problem Gossip-based protocols have no single points of failure Gossip-based protocols have no single points of failure However, naïve gossip-based protocols are vulnerable to targeted DoS attacks However, naïve gossip-based protocols are vulnerable to targeted DoS attacks Drum uses simple techniques to mitigate the effects of DoS attacks Drum uses simple techniques to mitigate the effects of DoS attacks Evaluations show Drum’s resistance to DoS Evaluations show Drum’s resistance to DoS The most effective attack against Drum is a broad one The most effective attack against Drum is a broad one General DoS-mitigation techniques: random ports and neighbor-selection General DoS-mitigation techniques: random ports and neighbor-selection Analysis and quantitative evaluation techniques may be applicable to other systems as well Analysis and quantitative evaluation techniques may be applicable to other systems as well DoS attacks are a real problem DoS attacks are a real problem Gossip-based protocols have no single points of failure Gossip-based protocols have no single points of failure However, naïve gossip-based protocols are vulnerable to targeted DoS attacks However, naïve gossip-based protocols are vulnerable to targeted DoS attacks Drum uses simple techniques to mitigate the effects of DoS attacks Drum uses simple techniques to mitigate the effects of DoS attacks Evaluations show Drum’s resistance to DoS Evaluations show Drum’s resistance to DoS The most effective attack against Drum is a broad one The most effective attack against Drum is a broad one General DoS-mitigation techniques: random ports and neighbor-selection General DoS-mitigation techniques: random ports and neighbor-selection Analysis and quantitative evaluation techniques may be applicable to other systems as well Analysis and quantitative evaluation techniques may be applicable to other systems as well

Gal BadishiFaculty of Electrical Engineering, TechnionMay 2004