exposing snooping in tor by hsdir relays · 2016-10-12 · 1. generate honions ho i ho j 3. build...

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Motivation Tor’s security relies on the honest behavior of relays Tor clearly states HSDirs should not snoop on onion services The behavior of HSDirs has not been studied Question: How to detect the snooping HSDirs and estimate a lower bound on them? Amirali Sanatinia , Guevara Noubir Northeastern University References 1) A. Sanatinia, G. Noubir, “Honey Onions: a Framework for Characterizing and Identifying Misbehaving Tor HSDirs”, IEEE Conference on Communications and Network Security (CNS), 2016 2) P. Winter, R. Kower, M. Mulazzani, M. Huber, S. Schrittwieser, S. Lindskog, E. Weippl, “Spoiled Onions: Exposing Malicious Tor Exit Relays”, Privacy Enhancing Technologies Symposium (PETS), 2015 A typical graph representation of the visited honions, and the hosting HSDirs. Tor Provides anonymity and privacy for users Hidden Services protect the anonymity of the servers 1. Generate honions ho i ho j 2. Place honions on HSDirs 3. Build bipartite graph On visit, mark potential HSDirs ho j d i d i+2 d i+1 d i d i+1 d i+2 On visit, add to bipartite graph The global map of detected misbehaving HSDirs and their most likely geographic origin. Exposing Snooping in Tor by HSDir Relays Honey Onions (HOnions) A framework to detect misbehaving Tor HSDir relays Each honion is a server program that logs visits Three schedules; daily, weekly, monthly (1500 per batch) Generate the bipartite graph of HSDirs and visited honions Identify the snooping HSDirs using the set cover problem NP- Complete problem Integer Linear Programming (ILP) Client Hidden Service IP RP HSDir (1) (2) (3) (4) (5) (6) (7) Flow diagram of the honion system. When a visit happens to one of the honions, after identifying the potential suspicious HSDirs, we add them to the bipartite graph. Hidden Services architecture. Results Identified more than 100 snooping HSDirs over the period of 72 days Logged about 40000 visits to the honions Wide range of probing, SQL injection, XSS, user enumeration, etc. More than 70% of the snoopers hosted on cloud, 25% were also exit nodes Top countries: USA, Germany, France, United Kingdom, and Netherlands The snoopers have adapted their techniques and increased their sophistication Conclusion and Future Work Malicious HSDirs have different level of sophistication Some delay visits to avoid detection as a tradeoff More than half of the misbehaving relays are hosted on cloud Some cloud providers accept bitcoins as payment These privacy infrastructures make the tracking more difficult The new trend of visits. The snoopers are delaying their visits to avoid identification.

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Page 1: Exposing Snooping in Tor by HSDir Relays · 2016-10-12 · 1. Generate honions ho i ho j 3. Build bipartite graph 2. Place honions on HSDirs On visit, mark potential HSDirs ho j d

Motivation• Tor’s security relies on the honest behavior of relays• Tor clearly states HSDirs should not snoop on onion services• The behavior of HSDirs has not been studied

Question: How to detect the snooping HSDirs and estimate a lower bound on them?

Amirali Sanatinia, Guevara NoubirNortheastern University

References1) A. Sanatinia, G. Noubir, “Honey Onions: a Framework for Characterizing and Identifying Misbehaving Tor

HSDirs”, IEEE Conference on Communications and Network Security (CNS), 20162) P. Winter, R. Kower, M. Mulazzani, M. Huber, S. Schrittwieser, S. Lindskog, E. Weippl, “Spoiled Onions:

Exposing Malicious Tor Exit Relays”, Privacy Enhancing Technologies Symposium (PETS), 2015

Atypicalgraphrepresentationofthevisitedhonions,andthehostingHSDirs.

Tor• Provides anonymity and privacy for users• Hidden Services protect the anonymity of the servers

1. Generate honions

hoi

hoj

2. Place honions on HSDirs3. Build bipartite graph

On visit, mark potential HSDirs

hoj

di

di+2

di+1

di

di+1

di+2

On visit, add to bipartite graph

TheglobalmapofdetectedmisbehavingHSDirs andtheirmostlikelygeographicorigin.

Exposing Snooping in Tor by HSDir Relays

Honey Onions (HOnions)• A framework to detect misbehaving Tor HSDir relays• Each honion is a server program that logs visits• Three schedules; daily, weekly, monthly (1500 per batch)• Generate the bipartite graph of HSDirs and visited honions• Identify the snooping HSDirs using the set cover problem• NP- Complete problem• Integer Linear Programming (ILP)

Client

Hidden Service

IP

RP

HSDir

(1)

(2)(3)

(4)

(5)

(6)

(7)

Flowdiagramofthehonion system.Whenavisithappenstooneofthehonions,afteridentifyingthepotentialsuspiciousHSDirs,weaddthemtothebipartitegraph.

HiddenServicesarchitecture.

Results• Identified more than 100 snooping HSDirs over the period of 72 days• Logged about 40000 visits to the honions• Wide range of probing, SQL injection, XSS, user enumeration, etc.• More than 70% of the snoopers hosted on cloud, 25% were also exit nodes• Top countries: USA, Germany, France, United Kingdom, and Netherlands• The snoopers have adapted their techniques and increased their sophistication

Conclusion and Future Work•Malicious HSDirs have different level of sophistication• Some delay visits to avoid detection as a tradeoff•More than half of the misbehaving relays are hosted on cloud• Some cloud providers accept bitcoins as payment• These privacy infrastructures make the tracking more difficult

Thenewtrendofvisits.Thesnoopersaredelayingtheirvisitstoavoididentification.