Instance Based Learning Model for Timing Analysis of Keystrokes to Perform Timing Attacks on the Secure Shell Protocol
Keywords:
Secure Shell, Authentication, Encrypting Key., Key strokesAbstract
The research present Instance Based Learning Model for timing analysis of keystrokes to perform timing attacks on the Secure Shell protocol. SSH is designed to provide a secure channel between two hosts. Despite the encryption and authentication mechanisms it uses, SSH has two weakness: First, the transmitted packets are padded only to an eight-byte boundary (if a block cipher is in use), which reveals the approximate size of the original data. Second, in interactive mode, every individual keystroke that a user types is sent to the remote machine in a separate IP packet immediately after the key is pressed, which leaks the inter-keystroke timing information of users’ typing. The research shows how these seemingly minor weaknesses result in serious security risks. The research picks up the ideas of Song et al.(2001) and show that there are problems with their practicability today. The research implements a countermeasure against timing attacks which it analyses and then shows a possibility to handle it. The research also presents a method to collect keystroke timing characteristics from users silently. Evaluation of Instance based learning and Hidden Markov Model was done to show how effective an Instance based learning model can handle timing analysis of keystrokes and timing attacks on secure shell.
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