Steganalysis

Steganalysis is the field that studies methods for detecting the presence of steganography, the practice of hiding messages within ordinary media so that the concealed data remains undisclosed. It serves as a counterpart to steganography and is a core area of information security and digital forensics.

Steganalysis investigates potential cover objects such as digital images, audio and video files, text documents, or network traffic. It can be passive, aiming to determine whether a steganographic payload exists, or active, attempting to reveal hidden data by interacting with the cover. Methods are typically categorized as universal (blind to the embedding method) or targeted (designed for specific embedding schemes).

Techniques include signature-based approaches that look for known embedding patterns, statistical and signal-processing analyses that detect anomalies introduced by embedding, and feature-based methods that extract high-dimensional descriptors from cover or stego samples. Modern approaches increasingly rely on machine learning and deep learning to distinguish stego from cover. Classic techniques in image steganalysis include chi-square tests, RS analysis, and co-occurrence measures applied to detect perturbations caused by embedding; in audio and video, changes to quantization, noise, and compression artifacts are exploited. In text, detection may rely on formatting and stylometric irregularities.

Performance is evaluated using metrics such as false positive rate, detection rate, accuracy, precision, recall, and ROC curves. Challenges include cover-source mismatch, adaptive and unknown embedding algorithms, and the effects of compression and resizing. Robust steganalysis requires representative datasets and benchmarks, as well as careful validation to avoid overfitting.

Applications span digital forensics, security auditing, and incident response. Datasets used for research and benchmarking, such as public image collections with known stego/cover pairs, support comparative evaluation of methods. See also steganography and digital forensics.