Skip to Main Content
Sensor pattern noises (SPN), extracted from digital images as device fingerprints, have been proved as an effective way for digital device identification. However, the limitation of the current method of extracting the sensor pattern noise is that the SPNs extracted from images are highly contaminated by the details from the scene and as a result the misclassification rate is high unless images of large size are used. In this work we propose a novel approach for enhancing sensor pattern noises so as to improve the performance of the identifier. The hypothesis underlying our fingerprint enhancer is that the stronger a signal component is, the less trustworthy the component should be and thus should be attenuated. An enhanced fingerprint can be obtained by assigning weighting factors inversely proportional to the magnitude of the signal components.