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SybilGuard: Defending Against Sybil Attacks via Social Networks Presented by: Sailesh Kumar Overview Introduction to sybil attack Graph Theoretic Model and Problem Formulation Overview of SybilGuard Complete Design Simulation Results and Analysis Conclusion ‹#› - Sailesh Kumar - 5/6/2017 Introduction to the Problem As the scale of a decentralized distributed system increases » Malicious behavior become a norm » If 1/3 nodes are malicious => no guarantee » Sybil attacks: a user takes multiple identities – Can easily create n/3 sybil nodes Using Central Authority » Can Control Sybil attacks » Worldwide trusted central authority is problematic » Central authority may become the bottleneck – DoS » May scare away potential users Defending against sybil attacks is difficult » IP address harvesting » Intelligent adversary ‹#› - Sailesh Kumar - 5/6/2017 Problem Formulation and Objective Social network » n honest human users » 1+ malicious users : multiple sybil identities Devise a defense system against sybil attacks » SybilGuard enables an honest node to identify other nodes » Verifier node V can verify if suspect node S is malicious Guaranteed bound on number of sybil groups » Divides n nodes into m equivalence classes » A group is sybil if it contains 1+ sybil nodes Guaranteed bound on size of sybil groups » In a group, at most w sybil nodes Completely decentralized » An honest node accepts honest nodes with high probability » Rejects malicious nodes with high probability » Accepts bounded number of sybil nodes ‹#› - Sailesh Kumar - 5/6/2017 Social Network Millions of users (nodes) Friends are connected by an edge (friends) » Usually degree of a nodes is small (~30) A malicious user fools an honest user » Creates an attack edge SybilGuard limits number of attack edges » Independent of number of sybil identities – Friends share a secret edge key – Edge keys are assigned out-of-band ‹#› - Sailesh Kumar - 5/6/2017 Trends Social networks are fast mixing Many sybil nodes disrupts this property » Creates a low quotient cut in the graph We assume that number of attack edges are few » Out-of-band edge creation » In real life a malicious user can not create many real friends » Multiple identities are not useful SybilGuard does not try to detect low quotient cuts but rather proposes an effective decentralized approach ‹#› - Sailesh Kumar - 5/6/2017 Random Routes Foundation of SybilGuard: different from random walk Random route begins at a random edge of a node At every node » For an incoming edge i, there is a unique outgoing edge j » Thus, input to output is one-to-one mapped A node A with d neighbors uniformly randomly chooses a permutation “x1,x2, . . . ,xd” among all permutations of 1,2, . . . ,d. If a random route comes from the ith edge, A uses edge xi as the next hop. ‹#› - Sailesh Kumar - 5/6/2017 Properties of Random Routes Convergence » Once two routes merge, they will remain merged Routes are back-traceable There can be only one route with length w that traverses e along the given direction at its ith hop If two random routes ever share an edge in the same direction, then one of them must start in the middle of the other Cycles can exist, but with low probability » Prob. (diameter k cycle) = 1/d(k-2) ‹#› - Sailesh Kumar - 5/6/2017 SybilGuard Algorithm node V: verify node S » V computes d random routes (length w) » S computes d random routes (length w) » If d/2 random routes intersects, accept S » Else reject S If few attack edges, then a sybil node’s random route is less likely to reach honest region And vice-versa ‹#› - Sailesh Kumar - 5/6/2017 SybilGuard Design Decentralized design Each node performs d random routes A node registers with all nodes along its random routes » Registration is done using public-private key ‹#› - Sailesh Kumar - 5/6/2017 SybilGuard Design Witness tables » Reverse registration table » Stores all downstream nodes along a random route – Registration table stores upstream nodes » This table also contains IP addresses of the nodes – Will see why? ‹#› - Sailesh Kumar - 5/6/2017 Validation Process (V verifies S) S sends all its witness tables to V V intersects its own witness tables with those of S If intersection point X » V contacts X (using IP address in witness table) » Authenticates with private key of X » Checks if V is present in X’s registry table » If yes, then this route accepts S If d/2 routes accept S, then V accepts S V X S ‹#› - Sailesh Kumar - 5/6/2017 Length of Random Routes It has been shown that » If w = Θ(√nlogn), then honest routes will intersect with high probability » Also the probability that a honest random route will reach sybil region is low Nodes locally determine w » Node A does small random walk and lets say reaches node B » A and B intersects their witness table » The distance m of first intersection point determines w » w = 2.1m » 2.1 is derived from analysis of Birthday Paradox distributions ‹#› - Sailesh Kumar - 5/6/2017 SybilGuard Dynamics Dealing with offline nodes » Bypass them » Use lookahead routing tables – Store information about next k hops Incremental routing table maintenance » New nodes only slightly changes current routing permutation » Like DHT ‹#› - Sailesh Kumar - 5/6/2017 Probability of Intersection Probability of intersection of honest routes » 1 million nodes » Node degree = 24 ‹#› - Sailesh Kumar - 5/6/2017 24 random routes, Accept if 10 intersections Probability of False Detection Probability that honest routes remain in honest region ‹#› - Sailesh Kumar - 5/6/2017 Discussion An honest node accepts other honest nodes with 99.8% prob? » How about remaining 0.2% probability? How to apply SybilGuard to completely virtual social networks where there are few real friends? Compromised computers » Hundreds of thousands » Millions of attacks edges » SybilGuard will fail Are Social networks indeed big or small? ‹#› - Sailesh Kumar - 5/6/2017