Reliable Bits Research Articles

Design of Robust, High-Entropy Strong PUFs via Weightless Neural Network

Physically unclonable functions (PUFs) have been explored as lightweight hardware primitives for the purpose of realizing robust security via strong authentication or secure key/ID generation. PUF harness manufacturing process variations for the purpose of generating binary keys or binary functions. An ideal strong PUF is a binary function that maps an m-bit input challenge to an uniquen-bit output response, making it attractive for authentication applications. Unfortunately, real strong PUF implementations suffer from reliability issues where the same challenge may produce different responses in the presence of noise. To overcome this problem, strong PUF leverages the availability of exponential number of challenge-response pairs (CRPs). A successful authentication event requires acquiring multiple CRPs and applying a threshold. In contrast, weak PUFs produce limited keys and are required to be highly reliable. Multiple techniques have been developed to achieve the necessary reliability. An additional prerequisite for strong PUFs is resilience against model-building attacks (cloning) by an adversary, who has observed a few CRPs, to prevent successful prediction of future CRPs. In this work, we first illustrate a strong PUF design that re-purposes a weightless neural network (WNN). Second, we showcase the robustness of WNN-based strong PUFs with respect to machine learning attacks, while providing desirable uniqueness and reliability metrics. Finally, we employ an initial entropy source of highly reliable weak PUF bits mapped to weightless neural networks (WNNs) for the purpose of creating a near-ideal strong PUF in terms of reliability. Our results show that it is possible to create highly reliable WNN–based strong PUFs with < 65 % ML accuracy by using as few as 32 initial reliable weak PUF bits.

Effective Combination of Iris-based Cancelable Biometrics and Biometric Cryptosystems

The fuzzy commitment scheme (FCS) is one of the most effective biometric cryptosystems (BCs) that provide secure management of cryptographic keys using biometric templates. In this scheme, error correcting codes (ECCs) are firstly employed to encode a cryptographic key into a codeword which is then secured via linking (committing) it with a biometric template of the same length. Unfortunately, the key length is constrained by the size of the adopted biometric template as well as the employed ECC(s). In this paper, we propose a secure iris template protection scheme that combines cancelable biometrics with the FCS in order to secure long cryptographic keys without sacrificing the recognition accuracy. First, we utilize cancelable biometrics to derive revocable templates of large sizes from the most reliable bits in iris codes. Then, the FCS is applied to the obtained cancelable iris templates to secure cryptographic keys of the desired length. The revocability of cryptographic keys as well as true iris templates is guaranteed due to the hybridization of both techniques. Experimental results show that the proposed hybrid system can achieve high recognition accuracy regardless of the key size.

A Fast Two-Phase Monte Carlo Method for Constructing Polar Codes With Arbitrary Binary Kernel

We propose a two-phase Monte Carlo (TPMC) method to accelerate the original Monte Carlo (MC) method for constructing polar codes with high-dimensional kernels. In the TPMC method, some of the most reliable and unreliable bits are obtained by Gaussian approximate-density evolution (GA-DE) method in the first phase; in the second phase, these most reliable and unreliable bits are viewed as frozen bits. Then, the MC method are used to evaluate the remaining bits and select some best bits from the remaining bits. Finally, these best bits and the most reliable bits are combined as the information bits of the constructed polar code. By our investigation, most bits can be fixed as frozen bits in the second phase without error performance loss of the constructed polar codes. Because computation of frozen bits can be saved and computation of the GA-DE method can be ignored in contrast to that of the MC method, the TPMC method substantially reduces the complexity of the MC method. Simulation results show that 1) For a G ⊗3 15 polar code with block length 3375 and code rate 1/2, the TPMC method can fix 3200 bits as frozen bits in the second phase without error performance loss, which reduces the computation cost by approximately 92.6% over the MC method; 2) Polar codes with high-dimensional kernels constructed by the TPMC method outperforms polar codes with the G 2 kernel constructed by the Tal-Vardy method in terms of error performance; 3) With the same computational cost, the TPMC method can construct better polar codes than the MC method.

ARUM: Polar-Coded HARQ Scheme Based on Incremental Channel Polarization

A hybrid automatic repeat request (HARQ) scheme for polar codes, called active-bit relocation under masks (ARUM), is proposed. In each transmission, the data bits are encoded and bitwisely XOR-masked using a binary vector before being transmitted through the channel. The masking process combines multiple transmissions together and forms another step of intertransmission channel transform. The reliabilities are updated after every transmission, and the less reliable bits in earlier ones are relocated to the more reliable positions at the latest transmitted block. ARUM is a very flexible HARQ scheme that allows varying mother code length and arbitrary rate-matching scheme. Simulation shows that ARUM can obtain near-optimal coding gain after combining multiple transmission blocks.

An Adaptive IR-HARQ Scheme for Polar Codes by Polarizing Matrix Extension

In this letter, we construct rate compatible polar codes via polarizing matrix extension, to support efficient adaptive incremental redundancy hybrid automatic repeat request (IR-HARQ) protocol. We show that an arbitrary number of incremental coded bits can be generated by extending the polarizing matrix, such that multiple retransmissions are aggregated to produce a longer polar code with extra coding gain. This coding gain is maximized by selecting the most reliable bit channels in the extended codes, rather than the shorter codes, as information bits. Naturally, some information bits are transferred from the shorter part to the extended part for higher bit channel reliability. One-to-one parity-checking between the two parts lends itself well to the above purpose during the construction of the longer code. Simulation results demonstrate consistent coding gain over the chase combining HARQ scheme.

Modified Iterative Decoding Algorithm for Polar Code Using Maximum Likelihood Estimation

The key challenges in real time voice communication in long term evolution mobile are reduction in complexity and latency. Efficient encoding and decoding algorithms can cater to these. The implementation of such polar code based efficient algorithms is proposed in this paper. The overall latency of 3.8 ms is needed to process 8 bit block length. The novel sub-matrix near to identity matrix is presented. This resulted into minimization of loops among least reliable bits due to iterated parity check matrix. Look-up table based memory mapping is used in encoder to reduce latency while Euclidian decoding technique is used in decoder. The number of iterations is reduced by 50%. The experimentation is performed with additive white Gaussian noise and QPSK modulation. The proposed modified iterative decoding algorithm requires SNR of 5.5 dB and 192 computations for targeted bit error rate of 10−4. The second proposed method needs 9 dB, 2 iterations for 384 computations. The penalty paid is quantization error of 0.63% due to restricting computations to fourth order series of hyperbolic function with same 8 bit block length.

Designing the optimal bit: balancing energetic cost, speed and reliability.

We consider the challenge of operating a reliable bit that can be rapidly erased. We find that both erasing and reliability times are non-monotonic in the underlying friction, leading to a trade-off between erasing speed and bit reliability. Fast erasure is possible at the expense of low reliability at moderate friction, and high reliability comes at the expense of slow erasure in the underdamped and overdamped limits. Within a given class of bit parameters and control strategies, we define ‘optimal’ designs of bits that meet the desired reliability and erasing time requirements with the lowest operational work cost. We find that optimal designs always saturate the bound on the erasing time requirement, but can exceed the required reliability time if critically damped. The non-trivial geometry of the reliability and erasing time scales allows us to exclude large regions of parameter space as suboptimal. We find that optimal designs are either critically damped or close to critical damping under the erasing procedure.

Enhanced belief propagation decoding of polar codes by adapting the parity-check matrix

Though the performance of belief propagation (BP) decoder for polar codes is comparable with the successive cancellation (SC) decoder, it has significant performance gap when compared with the improved SC decoders, such as SC list (SCL) decoding. In this paper, we propose an improved BP decoding for polar codes with good performance by adapting their parity-check matrices. The decoding process is iterative and consists of two parts. Firstly, the parity-check matrix of polar codes is adjusted such that one of its submatrices corresponding to less reliable bits is in a sparse nature. Secondly, the BP decoding is applied to the adjusted parity-check matrix. Simulation results show that the proposed decoder, when accompanied with the early termination scheme, provides significant performance gains over the original polar BP decoder under a relatively low decoding complexity and even competes with the cyclic redundancy check (CRC)-aided SCL (CRC-SCL) decoder only by increasing a tolerate complexity.

Optimal Generation of Iris Codes for Iris Recognition

The calculation of binary iris codes from feature values (e.g., the result of Gabor transform) is a key step in iris recognition systems. Traditional binarization method based on the sign of feature values has achieved very promising performance. However, currently, little research focuses on a deeper insight into this binarization method to produce iris codes. In this paper, we illustrate the iris code calculation from the perspective of optimization. We demonstrate that the traditional iris code is the solution of an optimization problem, which minimizes the distance between the feature values and the iris codes. Furthermore, we show that more effective iris codes can be obtained by adding terms to the objective function of this optimization problem. We investigate two additional objective terms. The first objective term exploits the spatial relationships of the bits in different positions of an iris code. The second objective term mitigates the influence of less reliable bits in iris codes. The two objective terms can be applied to the optimization problem individually, or in a combined scheme. We conduct experiments on four benchmark datasets with varying image quality. The experimental results demonstrate that the iris code produced by solving the optimization problem with the two additional objective terms achieves a generally improved performance in comparison to the traditional iris code calculated by binarizing feature values based on their signs.

A Power-Efficient Scheme for Wireless Sensor Networks Based on Transmission of Good Bits and Threshold Optimization

We propose a power-efficient transmission scheme for wireless sensor networks. In this scheme, the sensor nodes compress their corresponding source-relay channel state information (CSI) and transmit this compressed CSI sequence along with a selected subset of their received bits from the source, which we refer to as the good bits. We assume slowly varying fading channels between source and relays and analytically derive the compression rate of the CSI sequence. We then study the relay-fusion centre link and find an optimal threshold for our proposed scheme, based on the target bit error rate and the packet delivery ratio of the network. Combining the threshold optimization and the reliable bit transmission schemes, we study the total number of transmitted bits for our proposed system. We show that for slowly varying fading channels, our proposed scheme considerably reduces the number of transmitted bits, and consequently the transmission power of the relay nodes compared with a conventional scheme where all bits are transmitted to the fusion center. We also compare the performance of our proposed scheme with a special decode and forward (SDF) scheme previously introduced in the literature. In order to have a fair comparison, we modify the SDF scheme, such that the modified scheme includes the originally proposed SDF scheme as a special case. We provide detailed comparisons and discussions on the achieved bit error rate, energy efficiency, and feasibility of the proposed and the modified SDF schemes.

Exploring Smart Pilot for Wireless Rate Adaptation

Rate adaptation is an essential component in today’s wireless standards, which help approach the channel capacity and maximize the throughput. However, how to estimate the optimal data rate in a fluctuated channel remains of great concern. Previous wisdoms leverage PHY layer information for rate estimation, including confidence information like SoftPHY hints, and channel state information (CSI) measurements. However, when experiencing rapid time varying and frequency selective fading channel, the above metrics can be inaccurate. The reason roots from the fact that there are not enough cost-efficient pilots, which are pre-known symbols inserted in a packet for channel estimation. In this paper, we observe that by digging into both PHY layer decoder and upper layer protocol headers, more reliable data bits with high confidence level can be exploited. These data bits, termed smart pilot, can be used to calibrate the channel estimation measurements cost-efficiently. Based on the calibrated estimation, we further propose a novel greedy rate selection algorithm to track the optimal data rate, which successfully avoids the impact of deep fading subcarriers in both legacy 802.11a/g and 802.11n MIMO systems. Our experiments on GNU radio testbed show that SmartPilot quickly tracks the link variance, and improve the channel estimation accuracy by 87%. Furthermore, the trace driven simulation reveals that greedy rate selection algorithm predicts the data rate as good as the optimal rate adaptation algorithms for 802.11 standards.

A Cost/Speed/Reliability Tradeoff to Erasing

We present a Kullback–Leibler (KL) control treatment of the fundamental problem of erasing a bit. We introduce notions of reliability of information storage via a reliability timescale τ r , and speed of erasing via an erasing timescale τ e . Our problem formulation captures the tradeoff between speed, reliability, and the KL cost required to erase a bit. We show that rapid erasing of a reliable bit costs at least log 2 - log 1 - e - τ e τ r &gt; log 2 , which goes to 1 2 log 2 τ r τ e when τ r &gt; &gt; τ e .

A Low-Latency List Successive-Cancellation Decoding Implementation for Polar Codes

Due to their provably capacity-achieving performance, polar codes have attracted a lot of research interest recently. For a good error-correcting performance, list successive-cancellation decoding (LSCD) with large list size is used to decode polar codes. However, as the complexity and delay of the list management operation rapidly increase with the list size, the overall latency of LSCD becomes large and limits the applicability of polar codes in high-throughput and latency-sensitive applications. Therefore, in this work, the low-latency implementation for LSCD with large list size is studied. Specifically, at the system level, a selective expansion method is proposed such that some of the reliable bits are not expanded to reduce the computation and latency. At the algorithmic level, a double thresholding scheme is proposed as a fast approximate-sorting method for the list management operation to reduce the LSCD latency for large list size. A VLSI architecture of the LSCD implementing the selective expansion and double thresholding scheme is then developed, and implemented using a UMC 90 nm CMOS technology. Experimental results show that, even for a large list size of 16, the proposed LSCD achieves a decoding throughput of 460 Mbps at a clock frequency of 658 MHz.

Face Recognition and Template Protection with Shielding Function

Biometric authentication is the use of unique human features to provide a secure, reliable and convenient access to an environment or a computer system. However, there are numerous security and privacy concerns associated with the use of biometrics as a means of authentication. Unprotected biometric data can be used by an impostor to impersonate legitimate uses, to violate their privacy and steal their identity. This paper proposes a simplified, secure and privacy-preserving authentication scheme for face biometric based on modified shielding function. The modified shielding function is a simplified version of the generic shielding function which does not require additional preprocessing steps of quantization and reliable bit selection. Rotation invariant neighbour-based local binary pattern (RINLBP) is used to extract fixed length binary features directly from pre-processed face images. RINLBP is simple to calculate and has good performance. It is also robust against changes in illumination and image rotation. Concatenated error correction technique is used to address errors due to noise and intraclass variation. The concatenated technique corrects errors both block and bit errors in contrast to the generic shielding function in which only bit level errors are corrected. Results of experiments based on 200 face images obtained from the CASIA near infrared face database show a false acceptance rate of 0.47% and a false rejection rate of 1.56%. Our scheme has a key length of 120 bits, which is higher than the minimum requirement of 50 bits for biometric keys. It also has a large key space and entropy which makes it less susceptible to guessing attack (Pr =0.008).

Noise robustness of unpredictability in a chaotic laser system: toward reliable physical random bit generation.

We introduce a concept of noise robustness in dynamical systems with noise and argue that this concept is essential to guarantee the reliability of physical random bit generators (RBGs). As an example of promising physical RBGs we consider a chaotic laser system and show that it has the property of noise robustness with respect to changes in the temporal correlation of the noise source. Moreover, employing a simple model of tangent space dynamics, we give a theoretical interpretation of the numerical results and in particular show that the Lyapunov exponent determines a theoretical boundary of a noise-robust region in parameter space. These theoretical results are expected to be significant not only for chaotic lasers, but also for a broad class of chaotic dynamical systems with correlated noise.

Soft decision iterative error and erasure decoder for Reed–Solomon codes

A list decoding algorithm for iterative soft-decision decoding of Reed–Solomon (RS) codes is proposed in this study. The algorithm erases a combination of least reliable symbols and iteratively flips a new combination of least reliable bits in the received sequence. The symbol error correction capability of the algebraic hard decision RS decoder is extended up to the minimum Hamming distance of the code. A gain in performance is exhibited either at a lower or similar iteration complexity as compared to other iterative soft decision decoders of similar type. A complexity comparison with some of the comparable soft decision decoders is given. Simulation results for different modulation schemes and channel types are presented in this study for a comparison with other soft decision decoders of a similar kind.

Two Extended Programmable BCH Soft Decoders Using Least Reliable Bits Reprocessing

This paper proposes two Bose---Chaudhuri---Hocquenghem (BCH) soft decoders suitable for high-rate codes with medium to large word length. The proposed decoders extend the correcting capability by providing a programmable performance gain according to the choice of the extra compensated bits p, with a theoretical maximum likelihood decoding when 2t+p approaches the codeword size n, where t is the correcting capability of the code under algebraic decoding. Our proposed architectures for the proposed algorithms use pipelined arithmetic units, leading to a reduction in the critical paths. This allows for an increase in the operating frequency by up to m/2 times compared to algebraic decoders, where m is the Galois field size. Our proposed decoders operate only on the least reliable bits, which leads to a reduction in the decoder complexity by removing the Chien search procedure.

Adaptive decoding algorithm based on multiplicity of candidate sequences for Block Turbo Codes

It is known that Block Turbo Codes (BTC) can be nearly optimally decoded by Chase-II algorithm, in which the Least Reliable Bits (LRBs) are chosen empirically to keep the size of the test patterns (sequences) relatively small and to reduce the decoding complexity. While there are also other adaptive techniques, where the decoder's LRBs adapt to the external parameter of the decoder like SNR (Signal Noise Ratio) level, a novel adaptive algorithm for BTC based on the statistics of an internal variable of the decoder itself is proposed in this paper. Different from the previous reported results, it collects the statistics of the multiplicity of the candidate sequences, i.e., the number of the same candidate sequences with the same minimum squared Euclidean distance resulted from the decoding of test sequences. It is shown by Monte Carlo simulations that the proposed adaptive algorithm has only about 0.02dB coding loss but the average complexity of the proposed algorithm is about 42% less compared with Pyndiah's iterative decoding algorithm using the fixed LRBs parameter.

Improved High Code-Rate Soft BCH Decoder Architectures With One Extra Error Compensation

Compared with traditonal hard Bose-Chaudhuri-Hochquenghem (BCH) decoders, soft BCH decoders provide better error-correcting performance but much higher hardware complexity. In this brief, an improved soft BCH decoding algorithm is presented to achieve both competitive hardware complexity and better error-correcting performance by dealing with least reliable bits and compensating one extra error outside the least reliable set. For BCH (255, 239; 2) and (255, 231; 3) codes, our proposed soft BCH decoders can achieve up to 0.75-dB coding gain with one extra error compensation and 5% less complexity than the traditional hard BCH decoders.

Fast Chase Decoding Algorithms and Architectures for Reed–Solomon Codes

Chase decoding is a prevalent soft-decision decoding method for algebraic codes where an efficient bounded-distance decoder is available. Essentially, it repeatedly applies bounded-distance decoding upon combinatorially flipping certain least reliable bits (or patterns for nonbinary case). In this paper, we devise a one-pass Chase decoding algorithm of Reed-Solomon codes such that the desired error locator polynomial by flipping an error pattern is obtained in one pass (when operated in parallel) through utilizing the preceding results. This is effectively achieved through cumulative interpolation and linear-feedback-shift-register (LFSR) synthesis techniques. Furthermore, through converting the algorithm into the transform domain, exhaustive root search for each error locator polynomial is circumvented. Computationally, the new algorithm exhibits linear complexity , in attempting to determine a candidate codeword associated with each additionally flipped symbol/pattern; it compares favorably to quadratic complexity by straightforwardly utilizing hard-decision decoding, where and denote the code length and minimum distance, respectively. We also reveal a corrected algorithm for one-pass generalized minimum distance (GMD) decoding for Reed-Solomon codes from Koetter's original work. In addition, we devise a highly efficient one-pass Chase decoding algorithm for binary Bose-Chaudhuri-Hocquenghem (BCH) codes by taking advantage of a key characteristic of the Berlekamp algorithm. Finally, we present a systolic very large-scale integration (VLSI) decoder architecture through slightly compromising the proposed one-pass Chase decoding algorithm. It takes clock cycles to complete one iteration by flipping one error pattern. Both circuit and memory complexities are dictated by the dimension of flipping patterns; in particular, they are independent of the code length or the minimum distance , rendering it highly attractive for various applications.