1. Key-Stroke Timing and Timing Attack on SSH Yonit Shabtai and Michael Lustig supervisor: Yoram Yihyie Technion - Israel Institute of Technology Computer Networks Laboratory http:\\comnet.technion.ac.il/~cn19s01

2. SSH Overview SSH - protocol for secure network transmition. SSH replaces telnet,rsh,rlogin,ftp,etc… Provides authentication, integrity, encryption. Two different protocols: SSH1,SSH2 SSH protocol Client SSH protocol Client

3. SSH2 overview Transport layer –Secure channel - Diffie-Helman key exchange. –Server authentication - RSA/DSS signatures (CA opt.) –Encryption by CBC cyphers (3DES,Blowfish,…). –Integrity of data - Mac (HMAC-SHA1/MD5). User authentication layer –Integrity & confidentiality are assumed. –Two authentication methodes supported: Public key authentication (CA opt.) Password authentication Connection layer –Interactive login sessions, rexec, X11, TCP forwarding. –Multiplexing sessions into one channel. Padding length Random Padding Payload Integrity data (MAC) Packet length Optionally compressed encrypted Padding length Random Padding Payload Integrity data (MAC) Packet length

4. SSH weaknesses  Password is padded to 8 byte boundary (tracking short passwords)  In interactive mode, every keystroke is immediately sent in a separate IP packet. Keystroke timing leaks information!

5. Keystroke Attack on SSH

6. Hidden Markov Model Markov process HMM - A Markov model when the current state can not be observed. Outputs of the process are observed. Probability of output depends only on the state. Information on the prior path of the process can be inferred from it’s output. Motivation - efficient algorithms for working with HMM.

7. Keystroke Timing as HMM Character pair is the hidden state. Keystroke latency measured is the output observation. Two assumptions: –character sequence is uniformly distributed (holds for passwords). –Probability distribution of latency, depends only on the current state. q = character pair y = latency observation

8. Viterbi-Algorithm Widely used to solve HMM. The algorithm: –(y 1,…..,y T ) = observations of HMM. –(q 1,…..,q t ) = Most likely sequences. –S(q t ) most likely sequence,ending with q t with posteriori probability of V(q t ). Init : V(q 1 ) = P(q 1 |y 1 ) Iterate : V(q t ) = max (qt-1) P(y t |q t ) P(q t |q t-1 )V(q t-1 ) S(q t ) =argmax (qt-1) P(y t |q t ) P(q t |q t-1 )V(q t-1 ), 2  t  T

9. Viterbi Algorithm example The n-Viterbi algorithm. Output(1) Output(2)Output(3)

10. System Scheme AB Sniffer Detect SSH session detect nested SSH or SU n-Viterbi statistics Keystroke Timing Possibilities Password

11. Key stroke timing test A software that measures keystroke timing latencies and performs statistical operations was developed. We selected four letter keys, two number keys and two upper-case keys for the experiment i a k m 2 3 O J Using these keys we formed 64 key pairs. A user was asked to type each pair 30 times. The mean value, and variance of the latency was calculated for each pair.

12. Key stroke timing test results

13. Information Gain Analysis Attacker without prior knowledge: q  R Q H 0 [q] = -  q  Q Pr(q)log 2 [ Pr(q)] = log 2 [|Q|] = 6 [bits] Attacker knows latency y 0 of the keystroke of q  R Q H 1 [q|y=y 0 ] = -  q  Q Pr(q|y=y 0 )log 2 [ Pr(q|y=y 0 )]

14. Information Gain Estimation

15. Conclusions There are four types of timing distinguishable character pairs. Though the results are “optimistic”, it is shown that keystroke timing leaks a considerable amount of information. SSH is not secure as commonly believed.

16. The End http://comnet.technion.ac.il/~cn19s01