Network-based intruders seldom attack their victims directly from their own computer. Often, they stage their attacks through intermediate “stepping stones” in order to conceal their identity and origin. To distinguish the source of the attack behind the stepping stone(s), it is important to associate the incoming and outgoing flows or connections of a stepping stone. To resist attempts at correlation, the attacker may encrypt or otherwise manipulate the connection traffic.
Timing based correlation approaches shown to be quite effective in correlating encrypted connections. However, timing based correlation approaches are subject to timing perturbations that may be deliberately introduced by the attacker at stepping stones. In this project, our watermark-based approach is “active” in that, It embeds a unique watermark into the encrypted flows by slightly adjusting the planning of chosen bundles.
The one of a kind watermark that is inserted in the encrypted flow by lightly adjusting the timing of selected packets. The unique watermark that is embedded in the encrypted flow gives us a number of advantages over passive timing based correlation in resisting timing perturbations by the attacker. A two-fold monotonically increasing compound mapping is created and proved to yield more distinctive visible watermarks in the watermarked image. Security protection measures by parameter and mapping randomizations have also been proposed to deter attackers from illicit image recoveries.
Existing connection correlation approaches depend on three Different attributes:1) host activity; 2) connection content (i.e. packet payload); and 3) inter-packet timing attributes. The host activity-based approach gathers and tracks clients’ login activity at each stepping stone.
The goal of watermark-based correlation is to make the correlation of encrypted connections probabilistically robust against random timing perturbations by the adversary.
Unlike existing timing based correlation schemes, our watermark-based correlation is active in that it embeds a unique watermark into the encrypted flows, by somewhat adjusting the timing of selected packets.
If the embedded watermark is both unique and robust, the watermarked flows can be effectively identified and thus correlated at each stepping stone.
1. Watermark Bit Embedding and Decoding
2. Correlation Analysis
3. Watermark Tracing Model
4. Parameter and Mapping Randomization