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Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. In this paper, we study the problem of designing fingerprints that can withstand collusion, yet trace colluders. Since, in antipodal CDMA-type watermarking, the correlation contributions only decrease where watermarks differ, by constructing binary code vectors where any subset of k or fewer of these vectors have unique overlap, we may identify groups of k or less colluders. Our construction of such anti-collusion codes (ACC) uses the theory of combinatorial designs, and for n users requires O(√n) bits. Further, we explore a block matrix structure for the ACC that reduces the computational complexity for identifying colluders and improves the detection capability when colluders belong to the same subgroup.

In the future, many multicast services will take place in the wireless domain. However, before these services can successfully be deployed, security infrastructures must be developed that manage the keys needed to provide access control to content. We present a method for designing multicast key management trees that are suitable for mobile wireless environments. By matching the key management tree to the cellular network topology, the total communication burden is reduced by 33%-45% compared to using the traditional key management trees that are independent of the topology.

Digital fingerprinting is an effective method to identify users who might try to redistribute multimedia content, such as images and video. These fingerprints are typically embedded into the content using watermarking techniques that are designed to be robust to a variety of attacks. A cheap and effective attack against such digital fingerprints is collusion, where several differently marked copies of the same content are averaged or combined to disrupt the underlying fingerprint. We present a construction of collusion-resistant fingerprints based upon anti-collusion codes (ACC) and binary code modulation. ACC have the property that the composition of any subset of K or fewer codevectors is unique. Using this property, we build fingerprints that allow for the identification of groups of K or less colluders. We present a construction of binary-valued ACC under the logical AND operation using the theory of combinatorial designs. Our code construction requires only /spl Oscr/(/spl radic/n) orthogonal signals to accommodate n users. We demonstrate the performance of our ACC for fingerprinting multimedia by identifying colluders through experiments using real images.

In order to secure communication amongst members of a conference, a secret shared by all group members must be established. The Diffie-Hellman problem is often the basis for generating keys in two-party communication, and can also be used to establish conference keys. In heterogeneous networks, many conferences have participants of varying computational power and resources. Most conference keying schemes do not address this concern and place the same burden upon less-powerful clients as more-powerful ones. The establishment of conference keys should try to minimize the burden placed on more resource-limited users while ensuring that the entire group can establish the group secret. In this paper, we present a scheme for establishing a conference key using the two-party Diffie-Hellman scheme. The scheme is hierarchical, forming subgroup keys for successively larger subgroups en route to establishing the group key. A full, binary tree called the conference tree governs the order in which subgroup keys are formed. Key establishment schemes that consider users with varying costs or budgets are designed by appropriately choosing the conference tree. The tree that minimizes the total group cost is produced via the Huffman algorithm. A criterion is presented for the existence of a conference tree when users have varying budgets, and a greedy algorithm is presented that minimizes the total length of the conference tree under budget constraints.

Group-oriented services are attractive to both customers and service providers since they allow for potential markets that exploit user collaboration and shared experiences. In order to protect the content of a group service, the content must be encrypted using a key shared by group members. With the advancement of network technologies, customers will access group services from different networks using different terminals. The computational capabilities of the group members will vary. Contributory key agreement schemes have been developed to support secure communication between many senders and many receivers, but do not consider that users might require different amounts of time to perform a round of key establishment. In this paper, we develop a contributory key agreement scheme to setup the customer group which achieves a smaller latency for group key generation than existing schemes. We then address the latency needed to rekey the group during member joins and departures. A protocol that determines the location to place a joining member is presented that considers the time needed for rekeying the joining member as well as the effect the joining member has upon the departure times of the other group members. Simulations are presented that compare our algorithms with existing schemes for different group sizes, as well as different user join rates.

The 31 papers in this special issue focus on using the physical layer for securing the next generation of communication systems.

The lifting scheme is an effective method that provides flexible solutions for designing new perfect reconstruction filter bands. However, most of the existing applications of lifting are based upon stationary assumptions. As such, existing schemes tend to fit the data with a single, pre- determined model. These methods do not exploit the full flexibility provided by lifting. By exploiting the temporal interpretation of lifting, we incorporate adaptive filtering with the lifting scheme to cope with signals whose characteristics vary with time. In this paper, we study the proposed adaptive lifting scheme and its ability to decorrelate subbands. The decorrelation behavior is related proposed adaptive lifting scheme and its ability to decorrelate subbands. The decorrelation behavior is related to the coherence between the subbands, and simulations indicate improved decorrelation when compared with deterministic lifting. Our adaptive filterbank may be used in a thresholding scheme that can yield improved noise reduction capabilities compared to conventional wavelet thresholding schemes. We present a condition under which the proposed adaptive lifting denoising scheme can outperform a similar wavelet thresholding. Simulations are presented that indicate there is an SNR value at which the performance of adaptive lifting denoising surpasses wavelet denoising.© (2000) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

The lifting scheme is used as a motivational tool for designing a better temporal subband scheme in video coding. The new subband coding scheme replaces the typical Haar filterbank. A simple criterion is used for the detection of scene changes in video sequences, and a modification to the Haar lifting scheme is developed that allows for adjusting the filterbank near a scene change. The new edge adaptive lifting scheme is applied to a scene change in video data and achieves improved performance at scene change frames when compared with the lifting Haar filterbank.

A theory of frames that extend Gabor analysis by including chirping is discussed. The chirping parameterin these 'time-frequency localization frames' depends on time and/or frequency shift parameters that can beadapted to analyze and detect chirps in noisy signals. Radar/sonar applications are outlined. The frame theoryis motivated by a generalized notion of square-integrable group representation developed by Au, Antoine, andGazeau, together with ideas in Baraniuk's thesis on a metaplectic extension of Cohen's class.Keywords: chirps, frames, metaplectic group, time-frequency localization 1 INTRODUCTION Versatile time-frequency/time-scale algorithms like best basis or matching pursuits are excellent for denoising if one is content to let signal and noise be defined by the algorithm. However, when searching for specific typesof signals embedded in noise at high levels, one must possess a concrete a-priori idea of the signal one seeks. For such detection problems the philosophy of using a dictionary of time frequency localized patterns still makes

This paper will examine in brevity the matching pursuit algorithm proposed by Mallat and Zhang which yields an adaptive signal decomposition that may be used to derive a phase plane representation of a signal. Matching pursuits is closely related to wavelet analysis and may be considered a superset of wavelet multiresolution analysis. A methodology for coherent feature extraction, or denoising, using matching pursuits will be developed and explained. Acoustic signals derived from speech and music will be examined. Synthetic white noise and acoustic noise will be injected and matching pursuits will be used to attempt to remove noise from these signals.

Simple up slope propagation of underwater acoustic energy can usually be modeled by an adiabatic normal‐mode approximation, provided the slope is not too severe. Bottom interacting paths in such an environment are usually sufficiently attenuated to make consideration of mode coupling unnecessary. An environment further complicated by an offshore rise can cause additional acoustic energy to be introduced into lower‐order modes due to bottom interaction. These low‐order modes will then propagate in deep water until encountering the continental shelf. Experimental results from the Arctic Ocean between 25 and 45 Hz suggest such propagation conditions. These results, and their interpretation in the context of a coupled mode study will be presented. Emphasis will be placed on the conditions under which mode coupling will occur, and when it must be considered in prediction and localization problems. The coupled mode model, COUPLE [R. B. Evans, J. Acoust. Soc. Am. 74, 188–195 (1983)], is used as the vehicle for this study. Additional approximation schemes of obtaining a coupled mode result will be explored with the objective of obtaining a faster numerical solution. Comparisons will be made with adiabatic normal mode, and parabolic equations models.

Motivated by the human auditory system, a new signal transform is presented which models the way humans hear. Cochlear processing acts like a constant bandwidth bank of filters in the low‐frequency range but is of proportional bandwidth at higher frequencies. This new transform, which we call the composite wavelet transform, is better able to model this process than standard signal processing techniques such as the short‐time fourier transform (STFT) and the continuous wavelet transform (CWT). The composite wavelet transform in fact provides a signal analysis tool that is able to examine signals with competing signal structures whereas the STFT and the CWT do not. Numerical results for this transform are presented along with a comparison to the STFT and the CWT.

Motivated by the human auditory system, a new signal transform is presented which models the way humans hear. Cochlear processing acts like a constant bandwidth bank of filters in the low frequency range but is of proportional bandwidth at higher frequencies. This new transform, which we call the composite wavelet transform, is better able to model this process than standard signal processing techniques such as the short‐time Fourier transform (STFT) and the continuous wavelet transform (CWT). The composite wavelet transform in fact provides a signal analysis tool that is able to examine signals with competing signal structures whereas the STFT and the CWT do not. In order to insure stable signal recovery, the theory of frames is examined. An overview of the theory of frames will be given and wavelet and Gabor frames will be discussed. Recent work on frames for the composite wavelet transform will also be presented. Finally, some applications of frames, especially to speech signal processing will be consi...

This paper will examine in brevity the matching pursuit algorithm proposed by Mallat and Zhang, which yields an adaptive signal decomposition that may be used to derive a phase plane representation of a signal. Based on these ideas, and motivated by the application of wavelets to linear differential operators, a new numerical method for solving differential equations is proposed which is based on performing a matching pursuit algorithm in an operated dictionary. Using this new algorithm the nonhomogeneous Helmholtz differential operator with zero and nonzero boundary conditions shall be examined. A classical differential equation arising from acoustics shall be presented and solved using this new method. Results are presented for the one‐dimensional case, and the extension to higher dimensions is examined using the concept of tensor products to construct a dictionary for higher dimensional Hilbert spaces.