To pass messages between the two communicating parties (passive warden). False positives are the cases where the steganalysis tool incorrectly detects the presence of hidden content. A steganalyst is the one who applies steganalysis techniques for detecting hidden messages. Steganalysis is the art and science of detecting hidden contents. Stego-key is the key used in the embedding process and is required by the receiver for the extraction process of the secret message.
Stego-algorithm is the procedure of embedding the secret message into the cover-object. Stego-object is the modified cover-object after embedding the secret message in it. Digital Investigation 9 (2013) 235–245Īnd could be any digital media (text, image, video, audio, etc.). Cover-object is the carrier of the secret message Secret message is the information to be hidden. In this section we explain the terms we use in the rest of the paper. Basic terminology * Corresponding author. The main difference is that steganography focuses more on the imperceptibility property of the stego-object, while robustness is the main concern for digital watermarking.ġ.1. Steganography has some points in common with digital watermarking, they are both part of the larger field – information hiding, but there are differences between the two. Hiding of the message is done by embedding it into the object called the cover-object and the extraction of the message is done by feeding the stegoobject (cover-object þ secret message) and the key to the extraction algorithm. To perform steganography we need both an embedding and an extraction process. The main difference between steganography and cryptography is that the former tries to hide the very existence of the information exchange, while the latter is only interested in the secrecy of the exchanged contents, not of the exchange itself. It can be defined as the art and science of hiding secret messages in different media (images, audio, video, text, etc.) so that it can be correctly received by another party without raising suspicion by an observer (Chandramouli and Memon, 2003). Introduction The word steganography is derived from two Greek words (stegano and graphos) that respectively mean covered and writing. Keywords: Stegdetect Steganalysis Steganography Digital forensics Computer forensics Tool analysis False positivesġ. This method can be applied to any steganalysis tool, which gives the analyst a better understanding of the detection results, especially when he has no prior information about the false positive rate of the tool. Additionally, we have provided a detailed statistical analysis for the obtained results to study the difference in detection between selected groups, close groups and different groups of images. This should support the forensic expert to have better interpretation in their results, and taking the false positive rates into consideration.
The results obtained show that the rate of false positives generated by Stegdetect depends highly on the chosen sensitivity value, and it is generally quite high. The aim of this study is to help digital forensic analysts, aiming to study a large number of image files during an investigation, to better understand the capabilities and the limitations of steganalysis tools like Stegdetect. In doing so, we process more than 40,000 images randomly downloaded from the Internet using Google images, together with 25,000 images from the ASIRRA (Animal Species Image Recognition for Restricting Access) public corpus. In this paper we analyse Stegdetect, one of the well-known image steganalysis tools, to study its false positive rate. School of Computing, University of Portsmouth, Lion Terrace, Portsmouth PO1 3HE, UK School of Computing, University of Kent, UKĪrticle history: Received 3 October 2012 Received in revised form 8 January 2013 Accepted 24 January 2013 Contents lists available at SciVerse ScienceDirectĭigital Investigation journal homepage: A study on the false positive rate of Stegdetect Omed S.
0 kommentar(er)
