51 research outputs found

    Coding with Scrambling, Concatenation, and HARQ for the AWGN Wire-Tap Channel: A Security Gap Analysis

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    This study examines the use of nonsystematic channel codes to obtain secure transmissions over the additive white Gaussian noise (AWGN) wire-tap channel. Unlike the previous approaches, we propose to implement nonsystematic coded transmission by scrambling the information bits, and characterize the bit error rate of scrambled transmissions through theoretical arguments and numerical simulations. We have focused on some examples of Bose-Chaudhuri-Hocquenghem (BCH) and low-density parity-check (LDPC) codes to estimate the security gap, which we have used as a measure of physical layer security, in addition to the bit error rate. Based on a number of numerical examples, we found that such a transmission technique can outperform alternative solutions. In fact, when an eavesdropper (Eve) has a worse channel than the authorized user (Bob), the security gap required to reach a given level of security is very small. The amount of degradation of Eve's channel with respect to Bob's that is needed to achieve sufficient security can be further reduced by implementing scrambling and descrambling operations on blocks of frames, rather than on single frames. While Eve's channel has a quality equal to or better than that of Bob's channel, we have shown that the use of a hybrid automatic repeat-request (HARQ) protocol with authentication still allows achieving a sufficient level of security. Finally, the secrecy performance of some practical schemes has also been measured in terms of the equivocation rate about the message at the eavesdropper and compared with that of ideal codes.Comment: 29 pages, 10 figure

    Achieving the Capacity of any DMC using only Polar Codes

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    We construct a channel coding scheme to achieve the capacity of any discrete memoryless channel based solely on the techniques of polar coding. In particular, we show how source polarization and randomness extraction via polarization can be employed to "shape" uniformly-distributed i.i.d. random variables into approximate i.i.d. random variables distributed ac- cording to the capacity-achieving distribution. We then combine this shaper with a variant of polar channel coding, constructed by the duality with source coding, to achieve the channel capacity. Our scheme inherits the low complexity encoder and decoder of polar coding. It differs conceptually from Gallager's method for achieving capacity, and we discuss the advantages and disadvantages of the two schemes. An application to the AWGN channel is discussed.Comment: 9 pages, 7 figure

    Enhancing Multimodal Entity and Relation Extraction with Variational Information Bottleneck

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    This paper studies the multimodal named entity recognition (MNER) and multimodal relation extraction (MRE), which are important for multimedia social platform analysis. The core of MNER and MRE lies in incorporating evident visual information to enhance textual semantics, where two issues inherently demand investigations. The first issue is modality-noise, where the task-irrelevant information in each modality may be noises misleading the task prediction. The second issue is modality-gap, where representations from different modalities are inconsistent, preventing from building the semantic alignment between the text and image. To address these issues, we propose a novel method for MNER and MRE by Multi-Modal representation learning with Information Bottleneck (MMIB). For the first issue, a refinement-regularizer probes the information-bottleneck principle to balance the predictive evidence and noisy information, yielding expressive representations for prediction. For the second issue, an alignment-regularizer is proposed, where a mutual information-based item works in a contrastive manner to regularize the consistent text-image representations. To our best knowledge, we are the first to explore variational IB estimation for MNER and MRE. Experiments show that MMIB achieves the state-of-the-art performances on three public benchmarks

    Improved linear programming decoding of LDPC codes and bounds on the minimum and fractional distance

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    We examine LDPC codes decoded using linear programming (LP). Four contributions to the LP framework are presented. First, a new method of tightening the LP relaxation, and thus improving the LP decoder, is proposed. Second, we present an algorithm which calculates a lower bound on the minimum distance of a specific code. This algorithm exhibits complexity which scales quadratically with the block length. Third, we propose a method to obtain a tight lower bound on the fractional distance, also with quadratic complexity, and thus less than previously-existing methods. Finally, we show how the fundamental LP polytope for generalized LDPC codes and nonbinary LDPC codes can be obtained.Comment: 17 pages, 8 figures, Submitted to IEEE Transactions on Information Theor

    Instantly Decodable Network Coding: From Centralized to Device-to-Device Communications

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    From its introduction to its quindecennial, network coding has built a strong reputation for enhancing packet recovery and achieving maximum information flow in both wired and wireless networks. Traditional studies focused on optimizing the throughput of the system by proposing elaborate schemes able to reach the network capacity. With the shift toward distributed computing on mobile devices, performance and complexity become both critical factors that affect the efficiency of a coding strategy. Instantly decodable network coding presents itself as a new paradigm in network coding that trades off these two aspects. This paper review instantly decodable network coding schemes by identifying, categorizing, and evaluating various algorithms proposed in the literature. The first part of the manuscript investigates the conventional centralized systems, in which all decisions are carried out by a central unit, e.g., a base-station. In particular, two successful approaches known as the strict and generalized instantly decodable network are compared in terms of reliability, performance, complexity, and packet selection methodology. The second part considers the use of instantly decodable codes in a device-to-device communication network, in which devices speed up the recovery of the missing packets by exchanging network coded packets. Although the performance improvements are directly proportional to the computational complexity increases, numerous successful schemes from both the performance and complexity viewpoints are identified

    Geometrically robust perceptual fingerprinting: an asymmetric case

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    A masking method based on orthonormal spaces, protecting several bytes against both SCA and FIA with a reduced cost

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    In the attacker models of Side-Channel Attacks (SCA) and Fault Injection Attacks (FIA), the opponent has access to a noisy version of the internal behavior of the hardware. Since the end of the nineties, many works have shown that this type of attacks constitutes a serious threat to cryptosystems implemented in embedded devices. In the state-of-the-art, there exist several countermeasures to protect symmetric encryption (especially AES-128). Most of them protect only against one of these two attacks (either SCA or FIA). The main known counter-measure against SCA is masking; it makes the complexity of SCA growing exponentially with its order d. The most general version of masking is based on error correcting codes. It has the advantage of offering in principle a protection against both types of attacks (SCA and FIA), but all the functions implemented in the algorithm need to be masked accordingly, and this is not a simple task in general. We propose a particular version of such construction that has several advantages: it has a very low computation complexity, it offers a concrete protection against both SCA and FIA, and finally it allows flexibility: being not specifically dedicated to AES, it can be applied to any block cipher with any S-boxes. In the state-of-art, masking schemes all come with pros and cons concerning the different types of complexity (time, memory, amount of randomness). Our masking scheme concretely achieves the complexity of the best known scheme, for each complexity typ

    Torsion Limits and Riemann-Roch Systems for Function Fields and Applications

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    The Ihara limit (or -constant) A(q)A(q) has been a central problem of study in the asymptotic theory of global function fields (or equivalently, algebraic curves over finite fields). It addresses global function fields with many rational points and, so far, most applications of this theory do not require additional properties. Motivated by recent applications, we require global function fields with the additional property that their zero class divisor groups contain at most a small number of dd-torsion points. We capture this by the torsion limit, a new asymptotic quantity for global function fields. It seems that it is even harder to determine values of this new quantity than the Ihara constant. Nevertheless, some non-trivial lower- and upper bounds are derived. Apart from this new asymptotic quantity and bounds on it, we also introduce Riemann-Roch systems of equations. It turns out that this type of equation system plays an important role in the study of several other problems in areas such as coding theory, arithmetic secret sharing and multiplication complexity of finite fields etc. Finally, we show how our new asymptotic quantity, our bounds on it and Riemann-Roch systems can be used to improve results in these areas.Comment: Accepted for publication in IEEE Transactions on Information Theory. This is an extended version of our paper in Proceedings of 31st Annual IACR CRYPTO, Santa Barbara, Ca., USA, 2011. The results in Sections 5 and 6 did not appear in that paper. A first version of this paper has been widely circulated since November 200
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