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This work presents a lightweight, FPGA-based hardware implementation for polynomial multiplication, which is the major bottleneck in the NTRU public-key cryptographic scheme. NTRU is a quantum-resilient, lattice-based key exchange cryptosystem, and is currently a finalist in the ongoing National Institute of Standards and Technology post-quantum cryptography standardization. It is challenging to fit these quantum-resilient schemes into Internet of Things (IoT) sensor nodes due to the strict resource constraints (smaller area, less memory, and lower energy budgets) and the limited computational capabilities in embedded devices. We undertake this compact implementation for polynomial multiplication with two motivations: 1) constant-time implementation ensuring inherent security against timing side-channel attacks and 2) optimized hardware consumption to make it suitable for IoT applications. A single-step multiplexer-based iterative architecture is proposed to achieve both goals simultaneously. Compared to the architectures presented in the literature, our proposed work eliminates the utilization of a modular arithmetic unit and replaces it with the correct selection of input followed by an accumulator, which can help to save substantial device resources. Experimental results with an FPGA show that our proposed architecture achieves an area reduction of up to $2.86 \times $ and the throughput increase up to $1.23 \times $ compared to the state-of-the-art implementation strategies, providing comparable latency along with an inherent-timing attack resilience that is absent in several NTRU hardware implementation schemes. [ABSTRACT FROM AUTHOR]

Convolutional Neural Network (CNN) inference on a resource-constrained Internet-of-Things (IoT) device (i.e., ARM Cortex-M microcontroller) requires careful optimization to reduce the timing overhead. We propose two novel techniques to improve the computational efficiency of CNNs by targeting low-cost microcontrollers. Our techniques utilize on-chip memory and minimize redundant operations, yielding low-latency inference results on complex quantized models such as MobileNetV1. On the ImageNet dataset for per-layer quantization, we reduce inference latency and Multiply-and-Accumulate (MAC) per cycle by 22.4% and 22.9%, respectively, compared to the state-of-the-art mixed-precision CMix-NN library. On the CIFAR-10 dataset for per-channel quantization, we reduce inference latency and MAC per cycle by 31.7% and 31.3%, respectively. The achieved low-latency inference results can improve the user experience and save power budget in resource-constrained IoT devices. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) typically comprises sensors that have inadequate computational resources. On the contrary, blockchain technology is thought to be expensive in terms of resource consumption due to the consensus procedures involved. As a result, the application of blockchain to the IoT environment is a challenging task. The most appropriate solution lies in replacing the computationally heavy consensus algorithms with lightweight counterparts. Proof of authentication (PoAh) is the most suited replacement for such an environment. Several modifications have been proposed for PoAh during the last few years, and they are reviewed here. [ABSTRACT FROM AUTHOR]

Although the use of personal data from different contexts is essential to curbing the spread of COVID-19 in epidemic-handling systems (EHSs), it increases the chances of privacy breaches and personal data misuse. This article analyses the data lifecycle and proposes various technical requirements for privacy preservation in EHSs. [ABSTRACT FROM AUTHOR]

The Advanced Encryption Standard (AES) is a standardized block cipher widely used to protect data confidentiality. Besides that, it can be used to generate pseudo-random numbers, which has many important applications. Recently, several works demonstrated the efficient implementations of AES electronics code book (ECB) and counter (CTR) mode on GPU platforms, achieving high throughput. In this brief, we set a speed record of AES implementation, which outperformed previous implementations. In particular, the proposed AES implementation achieved throughput 9% (CTR) and 7% (ECB) higher than the state-of-the-art, bit-sliced implementation. Moreover, the proposed technique does not require round keys to be embedded into the code during compilation, which is a serious limitation found in earlier work. The proposed technique also achieved up to 63% higher throughput compared to another technique presented recently. Two use cases are presented here to verify the efficiency of the proposed AES implementation. Firstly, AES is used to generate random samples in a NIST post-quantum key encapsulation mechanism (KEM), achieving 3,350, 1,503 and 7,716 key exchanges per second on V100, T4, and RTX3080 GPUs respectively. This allows the proposed FrodoKEM implementation to be $2.99\times $ faster than the state-of-the-art performance. The proposed AES implementation was also used in an exhaustive key search application, achieving 11,428, 3,969, and 9,998 $\times 10^{6}$ encryptions per second on V100, T4, and RTX3080 GPUs, respectively. [ABSTRACT FROM AUTHOR]

Blockchain was introduced as an incorruptible distributed data structure for financial transactions. Its contents are intrinsically verifiable, it sustains its state over multiple nodes, and its property of consistent replication can be used to build an automated structure to control computational resources. [ABSTRACT FROM AUTHOR]

Predicate encryption is a public-key encryption that supports attribute-hiding as well as payload-hiding and achieves high flexibility in terms of access control. Since Katz, Sahai, and Waters first proposed the predicate encryption scheme in 2008, several predicate encryption schemes have been published. Unfortunately these are impractical as they require O(n) pairing computations for decryption with considerably large sized public parameters, secret key, and ciphertext, where n is the dimension of the attribute/predicate vectors. In this paper, we propose a very efficient predicate encryption scheme that requires only n exponentiation plus three pairing computations for decryption with shorter sized public parameters, secret key, and ciphertext. The proposed scheme is proven selective attribute-secure against chosen-plaintext attacks in the standard model under the Asymmetric Decisional Bilinear Diffie-Hellman assumptions. [ABSTRACT FROM AUTHOR]

The article discusses digital rights management (DRM). As currently implemented DRM prevents users from achieving interoperability across devices with the content they have purchased. After briefly reviewing early DRM technology and its current architecture, the author examines several varieties of interoperability including full-format, building-block-based, and transformation-driven. A discussion of the challenges that must be met before interoperability can be realized concludes with his recommendation that a new use model for DRM be adopted. INSET: FROM THE CONSUMER VIEW.