Web spoofing is a significant problem involving fraudulent email and web sites that trick unsuspecting users into revealing private information. We discuss some aspects of common attacks and propose a framework for client-side defense: a browser plug-in that examines web pages and warns the user when requests for data may be part of a spoof attack. While the plugin, SpoofGuard, has been tested using actual sites obtained through government agencies concerned about the problem, we expect that web spoofing and other forms of identity theft will be continuing problems in coming years. 1

We propose a novel and robust hashing paradigm that uses iterative geometric techniques and relies on observations that main geometric features within an image would approximately stay invariant under small perturbations. A key goal of this algorithm is to produce sufficiently randomized outputs which are unpredictable, thereby yielding properties akin to cryptographic MACs. This is a key component for robust multimedia identification and watermarking (for synchronization as well as content dependent key generation). Our algorithm withstands standard benchmark (e.g Stirmark) attacks provided they do not cause severe perceptually significant distortions. As verified by our detailed experiments, the approach is relatively media independent and works for audio as well.

Recently there has been significant development in the use of wavelet methods in various data mining processes. However, there has been written no comprehensive survey available on the topic. The goal of this is paper to fill the void. First, the paper presents a high-level data-mining framework that reduces the overall process into smaller components. Then applications of wavelets for each component are reviewd. The paper concludes by discussing the impact of wavelets on data mining research and outlining potential future research directions and applications.

Perceptual image hashing maps an image to a fixed length binary string based on the image's appearance to the human eye, and has applications in image indexing, authentication, and watermarking. In this paper, we present a general framework for perceptual image hashing using feature points. The feature points should be largely invariant under perceptually insignificant distortions. To satisfy this, we propose an iterative feature detector to extract significant geometry preserving feature points. We apply probabilistic quantization on the derived features to further enhance perceptual robustness. The proposed hash algorithm withstands standard benchmark (e.g. Stirmark) attacks including compression, geometric distortions of scaling and small angle rotation, and common signal processing operations. Content changing (malicious) manipulations of image data are also accurately detected.

Assuming that watermarking is feasible (say, against a limited set of attacks of significant interest), current methods use a secret key to generate and embed a watermark. However, if the same key is used to watermark different items, then each instance may leak partial information and it is possible that one may extract the whole secret from a collection of watermarked items. Thus it will be ideal to derive content dependent keys, using a perceptual hashing algorithm (with its own secret key) that is resistant to small changes and otherwise having randomness and unpredictability properties analogous to cryptographic MACs. The techniques

This paper develops a joint hashing/watermarking scheme in which a short hash of the host signal is available to a detector. Potential applications include content tracking on public networks and forensic identification. The host data into which the watermark is embedded are selected from a secret subset of the full-frame discrete cosine transform of an image, and the watermark is inserted through multiplicative embedding. The hash is a binary version of selected original image coefficients. We propose a maximum-likelihood watermark detector based on a statistical image model. The availability of a hash as side information to the detector modifies the posterior distribution of the marked coefficients. We derive Chernoff bounds on the receiver operating characteristic performance of the detector. We show that host-signal interference can be rejected if the hash function is suitably designed. The relative difficulty of an eavesdropper’s detection problem is also determined; the eavesdropper does not know the secret key used. Monte Carlo simulations are performed using photographic test images. Finally, various attacks on the watermarked image are introduced to study the robustness of the derived detectors. The joint hashing/watermarking scheme outperforms the traditional “hashless ” watermarking technique. Index Terms content-based retrieval, authentication, image watermarking, image hashing, detection theory, likeli-hood ratio test, Chernoff bounds, eavesdropping. I.

An image hash should be (1) robust to allowable operations and (2) sensitive to illegal manipulations (like image tampering) and distinct queries. Although existing methods try to address the first issue, the second issue has not been adequately looked into, primarily the issue of localizing tampering. This is primarily because of the difficulty in meeting two contradictory requirements. First, the hash should be small and second, to detect localized tampering, the amount of information in the hash about the original should be as large as possible. The desynchronization of the query with the original further aggravates the problem. Hence a tradeoff between these factors needs to be found. This paper presents an image hashing approach that is both robust and sensitive to not only detect but also localize tampering using a small signature (< 1kB). To our knowledge this is the first hashing method that can localize image tampering using a small signature that is not embedded into the image, like in watermarking. Index Terms — Locality preserving hashing, edge histogram, local region descriptors. 1.

Media hashing is an alternative approach to many applications previously accomplished with watermarking. The major disadvantage of the existing media hashing technologies is their poor resistance togeometric attacks. In this paper, a novel geometric distortion-invariant image hashing scheme which can be employed to perform copy detection and content authentication of digital images, is proposed. Our major contributions are threefold: (i) mesh-based robust hashing function is proposed � (ii) sophisticated hash database for error-resilient and fast matching is constructed� and (iii) the application scalability of our scheme for content copy tracing and authentication is studied. In addition, we further investigate several media hashing issues, including robustness and discrimination, error analysis, and complexity, for the proposed image hashing system. Exhaustive experimental results obtained from benchmark attacks con rm the excellent performance of the proposed method.

Digital watermarking appears today as an e cient mean of securing multimedia documents. Several application scenarios in the security of digital watermarking have been pointed out, each of them with di erent requirements. The three main identi ed scenarios are: copyright protection, i.e. protecting ownership and usage rights; tamper proo ng, aiming at detecting malicious modi cations; and authentication, the purpose of which is to check the authenticity of the originator of a document. While robust watermarks, which survive to any change or alteration of the protected documents, are typically used for copyright protection, tamper proo ng and authentication generally require fragile or semi-fragile watermarks in order to detect modi ed or faked documents. Further, most of robust watermarking schemes are vulnerable to the so-called copy attack, where a watermark can be copied from one document to another by any unauthorized person, making these schemes ine cient in all authentication applications. In this paper, we propose a hybrid watermarking method joining a robust and a fragile or semi-fragile watermark, and thus combining copyright protection and tamper proo ng. As a result this approach is at the same time resistant against copy attack. In addition, the fragile information is inserted in a way which preserves robustness and reliability of the robust part. The numerous tests and the results obtained according to the Stirmark benchmark demonstrate the superior performance of the proposed approach.

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