Aggregation‐tolerant steganography for data‐stream integrity verification

Abstract

Data outsourcing can make data-integrity protection a challenging task, especially when the trustworthiness of a third-party is unproven. A novel auditing process for integrity verification of data stream, whose storage and handling is outsourced to a third-party, is explored. For this purpose, the hidden information within this data that provides support for in-network data aggregation environments, such as sensor networks is masked. This mask is achieved by simultaneous embedding of several shifted watermark patterns into multiple data streams. The nature of this watermark allows it to be aggregated into a single data stream with minimal loss of this information. A great benefit of the proposed scheme is that the embedded watermarks are invariant to linear time-sequential or cross-stream aggregation operations, such as summation or averaging. Therefore, multiple data streams can be merged and at the same time, and the existence of each individual watermark within allowable bounds can still be verified. The simulation results show that the embedded watermarks can successfully be recovered with high confidence if proper hiding codes are chosen.

On the Properties of Non-Media Digital Watermarking: A Review of State of the Art Techniques

“…Before outsourcing, medical data undergo two consecutive steps ; the binning agent firstly bins the data to satisfy k-anonymity specification and secondly the watermark agent inserts watermark information in a hierarchical manner. Lately, Soltani Panah and van Schyndel [36] described an efficient watermark-based system for private data auditing; instead of delegating the task of data evaluation to a trusted third party, the proposed watermarking method verifies the trustworthiness of data whose storage and handling is outsourced to the cloud, by the entity/person that knows the embedded values.…”

“…2) Similarly, Soltani Panah and van Schyndel presented a high capacity low complexity watermarking scheme for ECG signals [36]. Given an ECG segment, a time-based sliding window is employed to find the local minimum and maximum data values in the current window to preserve those values during watermark insertion.…”