Geographic Data and Steganography - Using Google Earth and KML Files for High-Capacity Steganography

Abstract

Steganography is the art of hiding the existence of information, whereas cryptography only aims at hiding the content of a message. Most steganographic algorithms try to embed data into images, audio or video files that provide reasonable capacities. However, such systems are often vulnerable to simple statistical attacks. In this paper, in order to provide an appropriate alternative to the currently used algorithms, we examine the information hiding properties of vector data that is used by many geographic information systems in great quantities. Unlike watermarking, we focus on maximising embedding capacities rather than on robustness, while still providing security against statistical attacks. Our implementation that uses the KML format known from Google Earth and other map services can replace more than 20 % of the original data with hidden messages, provided that a lot of numerical geodata is present in the KML file. Thus, our algorithm can hide about twice as much as current algorithms for images. Yet, virtually no distortions are inflicted to the cover data. 1 STEGANOGRAPHY AND GEOGRAPHIC DATA Steganography is the art of hiding a message within an unsuspicious cover such that the message’s existence will not be detected by an adversary. Only the legitimate receiver shall be able to discover and extract the hidden message. In contrast, cryptographic algorithms merely try to hide the contents of a secret message. However, both steganography and cryptography use secret keys that solely the sender and the receiver possess1. Especially in the past two decades, many steganographic concepts and algorithms have been suggested for embedding data into images, video and audio files because these media are usually thought to provide enough redundancy to securely hide reasonable amounts of data. Steganography is not to be confused with wa1There also exist some so-called pure stegosystems for which no keys are needed. Unfortunately, every adversary can then extract hidden messages as soon as the used algorithm is known, so that these systems are not really advantageous (cf. (Katzenbeisser and Petitcolas, 2000)). termarking: Steganography’s main purpose is secret communication, while watermarking is used for copyright protection by inserting a few key-dependent bits into an object so that a watermark detector can identify that object as property of some person or enterprise. While the main focus in steganography is secrecy, a watermark is not required to be totally invisible; it is more important that the watermark cannot be removed without rendering the watermarked object unusable. In the recent years, geographic information systems (GIS) have been enjoying an increasing popularity. Besides professional applications that are, e. g., needed for spatial planning, internet or network-based services for route planners or topographic maps are attractive to many casual users. Many methods have been proposed to insert robust watermarks into polygons, shapes and other spatial objects which GISes rely upon. However, by now, using such geodata for steganographic communications with notable embedding capacities has not received much attention, although spatial objects are likely to provide enough noise to securely embed messages of practically usable lengths. Therefore, the objective of this paper is to examine how we can apply steganography to geodata and achieve both reasonable security against detection and high embedding capacities.

Extracted Key Phrases

8 Figures and Tables

Cite this paper

@inproceedings{Diehl2008GeographicDA, title={Geographic Data and Steganography - Using Google Earth and KML Files for High-Capacity Steganography}, author={Malte Diehl}, booktitle={SECRYPT}, year={2008} }