Attacks on Structured Peer-to-Peer Anonymous Communication Systems - - PowerPoint PPT Presentation
Motivation Anonymous Communication NISAN Torsk Conclusion Attacks on Structured Peer-to-Peer Anonymous Communication Systems Theresa Enghardt theri@mailbox.tu-berlin.de Seminar Computer Security Technische Universitt Berlin 28 July 2011
Motivation Anonymous Communication NISAN Torsk Conclusion
Theresa Enghardt
theri@mailbox.tu-berlin.de
Seminar Computer Security Technische Universität Berlin
28 July 2011
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Motivation Anonymous Communication NISAN Torsk Conclusion
Anonymous communication The identity of sender and recipient of a message in combination remain unknown to intermediate parties. → Intermediate nodes know at most one of the two establish Circuit: path of multiple nodes which relay messages possible: directory service using a Distributed Hash Table (DHT)
Chord - basis for NISAN Kademlia - basis for Torsk sophisticated security mechanisms still some vulnerabilities [1]
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Motivation Anonymous Communication NISAN Torsk Conclusion
Mix Nodes: I establishes a circuit through random nodes A, B and C Message wrapped in layers of encryption and relayed
Tor: Central directory service → Scalability problem DHT: lookup on random number of ID space to find a random node
I A B C R Message
Symmetric key
I: Initiator A: Entry Node B: Middle Node C: Exit Node R: Recipient
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
Chord: DHT protocol Node identifier N: hash, length m bit Key K: any random m-bit value [0..2m]: ID space directed circle K belongs to next N in the ring Chord ring N: Node identifier K: Key
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
Finger Table: Routing table, up to m entries i-th entry of node with ID n: node that belongs to key k = n + 2(i−1) Find_node(k): return entry closest to k Search terminates after m lookups Chord finger table
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
Threat model: Attacker controls fraction f of all nodes f ≤ 20% Attacks:
Passive attacks: Observe almost all lookups on the many queried malicious nodes → Link sender to recipient Active attacks: Send false information → Control the circuit
D E F G H I J K L M Network with 10 nodes,
f = 20%
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
NISAN: Chord + further security measures Against active attacks:
Aggregated greedy search for k: α lookups, aggregate results, maintain top list → protect from false answers Bounds checking: mean distance of “ideal” ith entry to actual entry
Against passive attacks:
Hide lookup target k, queried nodes return full table Still information leakage through range guessing (next slide) Random walks as alternative lookup, but not used Tradeoff between active and passive attacks active ones considered worse
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
Bounds estimation: search target k
Nodes before k all queried → lower bound: queried malicious node Node with ID > k will not be queried → upper bound: node known but not queried
finally selected node within at most m − 1 hops Range estimation of the finally selected node
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Motivation Anonymous Communication NISAN Torsk Conclusion Chord Threat model Design Vulnerabilities
Passive attack: Control exit node and trace back all lookups Attacker controls exit node C → Sees recipient’s identity Hop-by-hop tracing example: From B back to querier A
A performed lookup for T B was in top list, at most m − 1 hops before T L is lower bound of lookup, U is upper bound Find correct L for lookup on T, which is close to B L was contacted by A
A
L B T
U
Estimated range of lookup Lookups Select from top list
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Motivation Anonymous Communication NISAN Torsk Conclusion Kademlia Design Vulnerabilities
Kademlia: DHT with 160-bit opaque node IDs and keys closeness of IDs and keys: XOR metric - long common prefix binary tree routing tables: k-buckets, address range based on closeness iterative lookup
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Motivation Anonymous Communication NISAN Torsk Conclusion Kademlia Design Vulnerabilities
Torsk: Kademlia + Myrmic (certificates) nCert on each node:
Assigned by Neighborhood Authority (NA) when signing in Contains nList of neighbors (= ID space) Also stored on neighbor nodes to guarantee recency → Protects against nodes pretending to be close (active attacks) Contains rList of random nodes
Other active attack: Selective dropping of requests Passive attack: Information leakage Protect against both: Buddy mechanism - ask random other nodes to perform the lookup
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Motivation Anonymous Communication NISAN Torsk Conclusion Kademlia Design Vulnerabilities
Buddy selection: Search for buddy nodes by random walk
Yes Select new random node from nCert No Start over
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Motivation Anonymous Communication NISAN Torsk Conclusion Kademlia Design Vulnerabilities
I A Q B 1 2 3 4 Lookup through buddy:
Passive timing attack: Correlate lookups Protection with cover traffic:
Each node has lookup “slots” filled with random IDs Received lookup request replaces one of them Periodically perform lookup of all “slots” → No information is leaked
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Motivation Anonymous Communication NISAN Torsk Conclusion Kademlia Design Vulnerabilities
Active attack: Buddy exhaustion of honest middlemen → Prevent circuit extension Flood with lookup requests → uses up buddies, sabotate lookup for new ones Probability of stopping a random walk by providing false certificates
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Motivation Anonymous Communication NISAN Torsk Conclusion
NISAN:
Information leakage Longer circuits not an ideal solution (more malicious nodes) → Passive attacks possible
Torsk:
Sabotate honest circuits → Active attacks possible Improved buddy lookup: Go one step back when invalid certificate → DoS only slows down the process Block nodes who request too many lookups? DoS also possible on non-DHT systems
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Motivation Anonymous Communication NISAN Torsk Conclusion
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Motivation Anonymous Communication NISAN Torsk Conclusion
Anonymous and Secure Lookup.
second-generation onion router.
Chord: A Scalable Peer-to-Peer Lookup Service for Internet Applications.
information service for anonymization networks.
information system based on the xor metric.
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