Forward Chaining and Self-Embedding Watermarking for Tamper Detection in a Continuous Stream of Data

Abstract

Watermarking is extensively used in various media for data transfer, content authentication and integrity. The continuous flow of data is always vulnerable to tamper. This research proposes a new watermarking scheme that detects tampering in a stream of data. The stream of data is dynamically divided into different sized groups using synchronization points. A computed watermark is embedded in each group by hashing the concatenating the current group and the next group. A secondary watermark is generated based on the current group that prevents tampering from any attacks in the current group. Watermark verification table is used to determine all possible scenarios for false results. Experiments are performed to show its efficiency. False results decrease as the group size becomes larger. Random burst attacked requires larger group size. The scheme also shows with the increase in grouping parameter ‘m’ which defines the synchronization point, the false positive rate decreases.