Safely Measuring Tor. Rob Jansen U.S. Naval Research Laboratory Center for High Assurance Computer Systems
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1 Safely Measuring Tor Safely Measuring Tor, Rob Jansen and Aaron Johnson, In the Proceedings of the 23rd ACM Conference on Computer and Communication Security (CCS 2016). Rob Jansen Center for High Assurance Computer Systems Seminar Talk, October 21 st, 2016 DC-Area Anonymity, Privacy, and Security Seminar The George Washington University
2 Talk Overview Estimated ~1.75 M. Users/Day (metrics.torproject.org) Tor: an anonymous communication, censorship resistant, privacy-enhancing communication system How is Tor being used? being misused? performing? PrivCount: A Distributed System for Safely Measuring Tor 2
3 Talk Overview Estimated ~1.75 M. Users/Day (metrics.torproject.org) Tor: an anonymous communication, censorship resistant, privacy-enhancing communication system How is Tor being used? being misused? performing? Objective: To safely gather Tor network usage statistics Approach: Use distributed measurement, secure multiparty computation, and differential privacy PrivCount: A Distributed System for Safely Measuring Tor 3
4 Background and Motivation How Tor works Why measurements are needed and what to measure Measurement challenges
5 Background: Onion Routing Users Circuit Stream Relays Destinations PrivCount: A Distributed System for Safely Measuring Tor 5
6 Background: Using Circuits PrivCount: A Distributed System for Safely Measuring Tor 6
7 Background: Using Circuits 1. Clients begin all circuits with a selected guard PrivCount: A Distributed System for Safely Measuring Tor 7
8 Background: Using Circuits 1. Clients begin all circuits with a selected guard 2. Relays define individual exit policies PrivCount: A Distributed System for Safely Measuring Tor 8
9 Background: Using Circuits 1. Clients begin all circuits with a selected guard 2. Relays define individual exit policies 3. Clients multiplex streams over a circuit PrivCount: A Distributed System for Safely Measuring Tor 9
10 Background: Using Circuits 1. Clients begin all circuits with a selected guard 2. Relays define individual exit policies 3. Clients multiplex streams over a circuit 4. New circuits replace existing ones periodically PrivCount: A Distributed System for Safely Measuring Tor 10
11 Background: Using Circuits 1. Clients begin all circuits with a selected guard 2. Relays define individual exit policies 3. Clients multiplex streams over a circuit 4. New circuits replace existing ones periodically 5. Clients randomly choose relays, weighted by bandwidth PrivCount: A Distributed System for Safely Measuring Tor 11
12 Background: Directory Authorities Directory Authorities Hourly network consensus by majority vote Relay info (IPs, pub keys, bandwidths, etc.) Parameters (performance thresholds, etc.) PrivCount: A Distributed System for Safely Measuring Tor 12
13 Motivation: Why Measure Tor? Why are Tor network measurements needed? To understand usage behaviors to focus effort and resources To understand network protocols and calibrate parameters To inform policy discussion PrivCount: A Distributed System for Safely Measuring Tor 13
14 Motivation: Why Measure Tor? Why are Tor network measurements needed? To understand usage behaviors to focus effort and resources To understand network protocols and calibrate parameters To inform policy discussion Tor metrics are the ammunition that lets Tor and other security advocates argue for a more private and secure Internet from a position of data, rather than just dogma or perspective. Bruce Schneier ( ) PrivCount: A Distributed System for Safely Measuring Tor 14
15 Motivation: Measurement Challenges Some Existing Measurements Data Published Privacy Techniques Unsafe Inaccurate Relay BW available Test measurements Relay BW used Aggregated ~ 4 hours Total # daily users Inferred (consensus fetches) # users per country Aggregated ~ 24 hours, rounded, opt-in Exit traffic per port Aggregated ~ 24 hours, opt-in PrivCount: A Distributed System for Safely Measuring Tor 15
16 Motivation: Measurement Challenges Some Existing Measurements Safety concerns: Per-relay outputs Data stored locally No privacy proofs Data Published Privacy Techniques Unsafe Inaccurate Relay BW available Test measurements Relay BW used Aggregated ~ 4 hours Total # daily users Inferred (consensus fetches) # users per country Aggregated ~ 24 hours, rounded, opt-in Exit traffic per port Aggregated ~ 24 hours, opt-in PrivCount: A Distributed System for Safely Measuring Tor 16
17 Motivation: Measurement Challenges Some Existing Measurements Accuracy concerns: Per-relay noise Opt-in and inconsistent sampling Data Published Privacy Techniques Unsafe Inaccurate Relay BW available Test measurements Relay BW used Aggregated ~ 4 hours Total # daily users Inferred (consensus fetches) # users per country Aggregated ~ 24 hours, rounded, opt-in Exit traffic per port Aggregated ~ 24 hours, opt-in PrivCount: A Distributed System for Safely Measuring Tor 17
18 Motivation: Missing Measurements Many useful statistics are not collected for safety Users Total number of unique users at any time, how long they stay online, how often they join and leave, usage behavior Relays Total bandwidth capacity, congestion and queuing delays, circuit and other failures, denial of service and other attacks Destinations Popular destinations, popular applications, effects of DNS, properties of traffic (bytes and connections per page, etc.) PrivCount: A Distributed System for Safely Measuring Tor 18
19 Previous Measurement Studies Shining Light in Dark Places: Understanding the Tor Network McCoy et. al., PETS 2008 tcpdump of first 150 packet bytes (including 96 payload) Collected, stored, manually analyzed sensitive data Digging into anonymous traffic: A deep analysis of the Tor anonymizing network Repeated by Chaabane et. al., NSS 2010 Also used customized DPI software (OpenDPI) Similar ethical issues PrivCount: A Distributed System for Safely Measuring Tor 19
20 Previous Measurement Studies Shining Light in Dark Places: Understanding the Tor Network McCoy et. al., PETS 2008 tcpdump of first 150 packet bytes (including 96 payload) Collected, stored, manually analyzed sensitive data Digging into anonymous traffic: A deep analysis of the Tor anonymizing network Chaabane et. al., NSS 2010 Customized DPI software (OpenDPI) Similar ethical issues PrivCount: A Distributed System for Safely Measuring Tor 20
21 The PrivCount Measurement System PrivCount system architecture Distributed measurement and aggregation protocol Secure computation and private output
22 PrivCount: Overview Distributed measurement system Privacy-preserving counting system Tracks various types of Tor events, computes statistics from those events Based on PrivEx-S2 by Elahi et al. (CCS 2014) Distributes trust using secret sharing across many operators Achieves forward privacy during measurement the adversary cannot learn the state of the measurement before time of compromise Provides differential privacy of the results prevents confirmation of the actions of a specific user given the output PrivCount: A Distributed System for Safely Measuring Tor 22
23 PrivCount: Architecture Data Collectors (DCs) Collect events Increment counters DC1 DC2 PrivCount: A Distributed System for Safely Measuring Tor 23
24 PrivCount: Architecture Data Collectors (DCs) Collect events Increment counters DC1 DC2 Tally Server (TS) Central, untrusted proxy Collection facilitator TS PrivCount: A Distributed System for Safely Measuring Tor 24
25 PrivCount: Architecture Data Collectors (DCs) Collect events Increment counters DC1 DC2 Tally Server (TS) Central, untrusted proxy Collection facilitator TS Share Keepers (SKs) Stores DC secrets, sum for aggregation SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 25
26 PrivCount: Initialization DC1 DC2 Create deployment document Privacy parameters ε and δ Sensitivity for each statistic (max change due to single client) Noise weight ω (relative noise added by each DC) TS Deploy SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 26
27 PrivCount: Initialization Deploy DC1 DC2 Deploy Send to all DCs and SKs DCs and SKs accept only on unanimous consensus TS SK1 SK2 Deploy Deploy PrivCount: A Distributed System for Safely Measuring Tor 27
28 PrivCount: Configuration DC1 DC2 Create configuration document Collection start and end times Statistics to collect Estimated value for each statistic (maximize relative per-statistic accuracy while providing (ε, δ)- differential privacy) SK1 TS SK2 Config PrivCount: A Distributed System for Safely Measuring Tor 28
29 PrivCount: Configuration Config DC1 DC2 Config Send to all DCs and SKs DCs and SKs check for consistency TS SK1 SK2 Config Config PrivCount: A Distributed System for Safely Measuring Tor 29
30 PrivCount: Execution - Setup DC1 DC2 N_DC1 N_DC2 Generate noise for each counter N ~ Normal(0,ωσ) mod q Contributes to differential privacy of the outputs TS SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 30
31 PrivCount: Execution - Setup S1_DC1 S2_DC1 DC1 DC2 S1_DC2 S2_DC2 N_DC1 N_DC2 Generate random share for each SK S ~ Uniform({0,, q-1}) Blinds the actual counts for forward privacy at the DCs TS SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 31
32 PrivCount: Execution - Setup S1_DC1 S2_DC1 DC1 DC2 S1_DC2 S2_DC2 N_DC1 N_DC2 DCs send shares to SKs TS S1_DC1 S1_DC2 SK1 SK2 S2_DC1 S2_DC2 PrivCount: A Distributed System for Safely Measuring Tor 32
33 PrivCount: Collection C_DC1 C_DC2 S1_DC1 S2_DC1 DC1 DC2 S1_DC2 S2_DC2 N_DC1 N_DC2 DCs collect events and increment counters TS S1_DC1 S1_DC2 SK1 SK2 S2_DC1 S2_DC2 PrivCount: A Distributed System for Safely Measuring Tor 33
34 PrivCount: Collection C_DC1 C_DC2 S1_DC1 S2_DC1 DC1 DC2 S1_DC2 S2_DC2 N_DC1 N_DC2 Send Counters to TS No privacy lost as long as 1 SK is honest TS S1_DC1 S1_DC2 SK1 SK2 S2_DC1 S2_DC2 PrivCount: A Distributed System for Safely Measuring Tor 34
35 PrivCount: Aggregation DC1 DC2 TS combines all counter values from DCs and SKs Subtracts SK-held values from DC-held values TS C_DC1 S1_DC1 S2_DC1 N_DC1 + C_DC2 S1_DC2 S2_DC2 N_DC2 - - S1_DC1 S1_DC2 S2_DC1 S2_DC2 SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 35
36 PrivCount: Aggregation DC1 DC2 TS combines all counter values from DCs and SKs Subtracts SK-held values from DC-held values TS C_DC1 S1_DC1 S2_DC1 N_DC1 C_DC2 + S1_DC2 - S2_DC2 N_DC2 S1_DC1 S1_DC2 S2_DC1 S2_DC2 SK1 SK2 PrivCount: A Distributed System for Safely Measuring Tor 36
37 PrivCount: Aggregation DC1 DC2 Results are differentially private and safe to publish TS C_DC1 C_DC2 SK1 SK2 N_DC1 N_DC2 PrivCount: A Distributed System for Safely Measuring Tor 37
38 Deployment and Measurement Results Configuring and running Tor relays Exploratory measurements using various exit policies In-depth measurements of most popular usage Network-wide measurement inference
39 Deploying PrivCount DC1 DC2 DC3 DC4 DC5 DC6 DC % entry bandwidth TS 1.099% exit bandwidth SK1 SK2 SK3 SK4 SK5 SK6 PrivCount: A Distributed System for Safely Measuring Tor 39
40 Collection Phases Exploratory phases Explore various exit policies (strict, default, open) Explore various applications (web, interactive, other) Gather only totals (circuits, streams, bytes) Use Tor metrics to estimate input parameters Run for 1 day, iterate In-depth phases Focus on most popular exit policy and applications Gather totals and histograms Use exploratory results to estimate input parameters Run for 4 days for client stats, 21 days for exit stats PrivCount: A Distributed System for Safely Measuring Tor 40
41 Results: Exit Policies Number of Circuits Traffic by Exit Policy 10 6 Default Open Strict Number of Streams Default Open Strict Open file sharing ports reduce web data transferred Interactive Web Other Data Transferred (GiB) Default Open Strict PrivCount: A Distributed System for Safely Measuring Tor 41
42 Results: Amount and Types of Traffic 100 Interactive Web Other 100 Increase in web traffic Connections (%) Bytes (%) [1] PETS 2008, McCoy... [2] NSS 2010, Chaabane...[3] CCS 2016, Jansen... PrivCount: A Distributed System for Safely Measuring Tor 42
43 Results: Number of Unique Users Unique Users (10 Minutes) Total Active Inactive Active 710,000 total users 550,000 active users In an average 10 mins. PrivCount: A Distributed System for Safely Measuring Tor 43
44 Results: Number of Unique Users Unique Users (10 Minutes) Total Active Inactive Active 710,000 total users 550,000 active users In an average 10 mins. ~1,750,000 daily users (Consensus downloads PrivCount: A Distributed System for Safely Measuring Tor 44
45 Results: Number of Unique Users Unique Users (10 Minutes) Total Active Inactive Active 710,000 total users 550,000 active users In an average 10 mins. ~1,750,000 daily users (Consensus downloads ~800,000 ~1,600,000 average concurrent users (Tor Browser update pings - webstats2/) PrivCount: A Distributed System for Safely Measuring Tor 45
46 Results: Traffic Modeling Statistics PrivCount: A Distributed System for Safely Measuring Tor 46
47 Conclusion Distributed measurement for Tor Improve accuracy, safety, security Allow us to collect more statistics Open source: Future measurement plans Network traffic to produce models that can be used to generate realistic traffic Onion services to improve reliability and scalability Better techniques for cardinality (e.g., # unique users) Detecting denial of service attacks and other misbehavior Contact rob.g.jansen@nrl.navy.mil, PrivCount: A Distributed System for Safely Measuring Tor 47
48 Questions
49 Privacy Parameters for (ε, δ)-differential privacy ε = 0.3 : same as used by Tor onion service stats δ = 10-3 : upper bound on prob. of choosing noise value that violates ε-differential privacy DCs on 3 machines, add 3x noise User action bounds Action Simultaneous open entry connections 1 Entry connection open time New entry connections 12 New circuits 146 Bound 24 hours New streams 30,000 Data sent or received 10 MiB PrivCount: A Distributed System for Safely Measuring Tor 49
50 PrivCount vs PrivEx How does PrivCount enhance PrivEx Multi-phase iterative measurement Expanded privacy notion that simultaneously handles multiple types of measurements Optimal allocation of the ε privacy budget across multiple statistics Composable security definition and proof More capable and reliable tool Supports over 30 different types of Tor statistics Resilience to node failures and reboots Simpler configuration and setup PrivCount: A Distributed System for Safely Measuring Tor 50
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