The context-tree weighting method: extensions

First we modify the basic (binary) context-tree weighting method such that the past symbols x1-D, x2-D, …, x 0 are not needed by the encoder and the decoder. Then we describe how to make the context-tree depth D infinite, which results in optimal redundancy behavior for all tree sources, while the number of records in the context tree is not larger than 2T-1. Here T is the length of the source sequence. For this extended context-tree weighting algorithm we show that with probability one the compression ratio is not larger than the source entropy for source sequence length T¿8 for stationary and ergodic source

Faster universal modeling for two source classes

The Universal Modeling algorithms proposed in [2] for two general classes of finite-context sources are reviewed. The above methods were constructed by viewing a model structure as a partition of the context space and realizing that a partition can be reached through successive splits. Here we start by constructing recursive counting algorithms to count all models belonging to the two classes and use the algorithms to perform the Bayesian Mixture. The resulting methods lead to computationally more efficient Universal Modeling algorithms

Semantic Coding: Partial Transmission

Shannon wrote in 1948: rdquoThe semantic aspects of communication are irrelevant to the engineering problemrdquo. He demonstrated indeed that the information generated by a source depends only on its statistics and not on the meaning of the source output. The authors derived the fundamental limits for semantic compaction, transmission and compression systems recently. These systems have the property that the codewords are semantic however, i.e. close to the source sequences. In the present article we determine the minimum distortion for semantic partial transmission systems. In these systems only a quantized version of each source source symbol is transmitted to the receiver. It should be noted that our achievability proof is based on weak instead of strong typicality. This is unusual for Gelfand-Pinsker [1980] related setups as e.g. semantic coding and embedding

Signaling over arbitrarily permuted parallel channels

The problem of transmission of information over arbitrarily permuted parallel channels is studied here. The transmitter does not know over which channel a certain code-sequence will actually be transmitted, however the receiver knows how the sequences are permuted. The permutation is arbitrary but constant during the (simultaneous) transmission of the code-sequences via the parallel channels. It is shown first that the sum of the capacities of each channel is achievable for such a communication system in the special case where the capacity achieving input distributions of all channels are identical. More important is that this sum-capacity can also be achieved using a single channel code for all channels combined with a sequential decoding method. The construction of a rate-matching code based on maximum distance separable (MDS) codes turns out to be crucial. Finally, the case where the parallel channels have different capacity-achieving input distributions is investigated. Also for this case the capacity is determined. Again, this capacity is achievable with a sequential decoding procedure

Semantic Coding: Partial Transmission

Shannon wrote in 1948: rdquoThe semantic aspects of communication are irrelevant to the engineering problemrdquo. He demonstrated indeed that the information generated by a source depends only on its statistics and not on the meaning of the source output. The authors derived the fundamental limits for semantic compaction, transmission and compression systems recently. These systems have the property that the codewords are semantic however, i.e. close to the source sequences. In the present article we determine the minimum distortion for semantic partial transmission systems. In these systems only a quantized version of each source source symbol is transmitted to the receiver. It should be noted that our achievability proof is based on weak instead of strong typicality. This is unusual for Gelfand-Pinsker [1980] related setups as e.g. semantic coding and embedding

Privacy leakage in biometric secrecy systems

Motivated by Maurer [1993], Ahlswede and Csiszar [1993] introduced the concept of secret sharing. In their source model two terminals observe two correlated sequences. It is the objective of both terminals to form a common secret by interchanging a public message (helper data), that should contain only a negligible amount of information about the secret. Ahlswede and Csiszar showed that the maximum secret key rate that can be achieved in this way is equal to the mutual information between the two source outputs. In a biometric setting, where the sequences correspond to the enrollment and authentication data, it is crucial that the public message leaks as little information as possible about the biometric data, since compromised biometric data cannot be replaced. We investigate the fundamental trade-offs for four biometric settings. The first one is the standard (Ahlswede-Csiszar) secret generation setting, for which we determine the secret key rate - privacy leakage region. Here leakage corresponds to the mutual information between helper data and biometric enrollment sequence conditional on the secret. In the second setting the secret is not generated by the terminals but independently chosen, and transmitted using a public message. Again we determine the region of achievable rate - leakage pairs. In setting three and four we consider zero-leakage, i.e. the public message contains only a negligible amount of information about the secret and the biometric enrollment sequence. To achieve this a private key is needed which can be observed only by the terminals. We consider again both secret generation and secret transmission and determine for both cases the region of achievable secret key rate - private key rate pairs

On the security of XOR-method in biometric authentication systems

A biometric authentication system can be partitioned into a layer that extracts common randomness out of a pair of related biometric sequences [Maurer, 1993] and a layer that masks a key sequence with this common randomness. We will analyze the performance of such a layered system first, and will show that an alternative method, the XOR- echnique, is not always secure