scholarly journals The QARMA Block Cipher Family. Almost MDS Matrices Over Rings With Zero Divisors, Nearly Symmetric Even-Mansour Constructions With Non-Involutory Central Rounds, and Search Heuristics for Low-Latency S-Boxes

2017 ◽  
pp. 4-44 ◽  
Author(s):  
Roberto Avanzi
Keyword(s):  
Hash Function ◽  
Block Cipher ◽  
State Of The Art ◽  
Critical Path ◽  
Low Latency ◽  
New Family ◽  
Zero Divisors ◽  
Search Heuristics ◽  
Universal Hash Function ◽  
Block Sizes

This paper introduces QARMA, a new family of lightweight tweakable block ciphers targeted at applications such as memory encryption, the generation of very short tags for hardware-assisted prevention of software exploitation, and the construction of keyed hash functions. QARMA is inspired by reflection ciphers such as PRINCE, to which it adds a tweaking input, and MANTIS. However, QARMA differs from previous reflector constructions in that it is a three-round Even-Mansour scheme instead of a FX-construction, and its middle permutation is non-involutory and keyed. We introduce and analyse a family of Almost MDS matrices defined over a ring with zero divisors that allows us to encode rotations in its operation while maintaining the minimal latency associated to {0, 1}-matrices. The purpose of all these design choices is to harden the cipher against various classes of attacks. We also describe new S-Box search heuristics aimed at minimising the critical path. QARMA exists in 64- and 128-bit block sizes, where block and tweak size are equal, and keys are twice as long as the blocks. We argue that QARMA provides sufficient security margins within the constraints determined by the mentioned applications, while still achieving best-in-class latency. Implementation results on a state-of-the art manufacturing process are reported. Finally, we propose a technique to extend the length of the tweak by using, for instance, a universal hash function, which can also be used to strengthen the security of QARMA.

scholarly journals Orthros: A Low-Latency PRF

2021 ◽  
pp. 37-77
Author(s):  
Subhadeep Banik ◽  
Takanori Isobe ◽  
Fukang Liu ◽  
Kazuhiko Minematsu ◽  
Kosei Sakamoto
Keyword(s):  
Hardware Implementation ◽  
Block Cipher ◽  
State Of The Art ◽  
Security Analysis ◽  
Parallel Structure ◽  
Low Latency ◽  
Round Function ◽  
Minimum Latency ◽  
Primary Focus ◽  
Pseudorandom Function

We present Orthros, a 128-bit block pseudorandom function. It is designed with primary focus on latency of fully unrolled circuits. For this purpose, we adopt a parallel structure comprising two keyed permutations. The round function of each permutation is similar to Midori, a low-energy block cipher, however we thoroughly revise it to reduce latency, and introduce different rounds to significantly improve cryptographic strength in a small number of rounds. We provide a comprehensive, dedicated security analysis. For hardware implementation, Orthros achieves the lowest latency among the state-of-the-art low-latency primitives. For example, using the STM 90nm library, Orthros achieves a minimum latency of around 2.4 ns, while other constructions like PRINCE, Midori-128 and QARMA9-128- σ0 achieve 2.56 ns, 4.10 ns, 4.38 ns respectively.

scholarly journals CFA: A New Family of Hybrid CA-Based PRNGs

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Fatima Ezzahra Ziani ◽  
Anas Sadak ◽  
Charifa Hanin ◽  
Bouchra Echandouri ◽  
Fouzia Omary
Keyword(s):  
Cellular Automata ◽  
Cellular Automaton ◽  
Hash Function ◽  
Block Cipher ◽  
General Structure ◽  
Security Analysis ◽  
Pseudorandom Number Generator ◽  
Number Generator ◽  
Cryptographic Primitives ◽  
New Family

In this article, a new Pseudorandom Number Generator (PRNG) construction is proposed. It is based on cellular automata (CAs) and comprises other cryptographic primitives organized as blocks. Each of these blocks has a purpose and serves toward obtaining a higher level of randomness. The construction described is modular, and each of its blocks can be replaced, modified, or adapted according to the user, the application, or the level of randomness required. The authors first describe a general structure and the design principles behind each of the components. Next, a concrete example using the SHA-3 hash function, a hybrid cellular automaton, and the AES block cipher is provided. Then, the security analysis and the statistical properties for this specific instance of the scheme are presented.

The smallest extraction problem

2021 ◽  
Vol 14 (11) ◽  
pp. 2445-2458
Author(s):  
Valerio Cetorelli ◽  
Paolo Atzeni ◽  
Valter Crescenzi ◽  
Franco Milicchio
Keyword(s):  
Unsupervised Learning ◽  
Optimization Problem ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Data Extraction ◽  
Source Code ◽  
Web Data ◽  
Web Data Extraction ◽  
New Family ◽  
Context Free

We introduce landmark grammars , a new family of context-free grammars aimed at describing the HTML source code of pages published by large and templated websites and therefore at effectively tackling Web data extraction problems. Indeed, they address the inherent ambiguity of HTML, one of the main challenges of Web data extraction, which, despite over twenty years of research, has been largely neglected by the approaches presented in literature. We then formalize the Smallest Extraction Problem (SEP), an optimization problem for finding the grammar of a family that best describes a set of pages and contextually extract their data. Finally, we present an unsupervised learning algorithm to induce a landmark grammar from a set of pages sharing a common HTML template, and we present an automatic Web data extraction system. The experiments on consolidated benchmarks show that the approach can substantially contribute to improve the state-of-the-art.

Deep Learning Model for Imbalanced Multi-label Surface Defect Classification

2021 ◽  
Author(s):  
Yang Liu ◽  
Yachao Yuan ◽  
Jing Liu
Keyword(s):  
Deep Learning ◽  
Surface Defect ◽  
State Of The Art ◽  
Steel Production ◽  
Learning Model ◽  
The State ◽  
Low Latency ◽  
Defect Classification ◽  
Key Techniques ◽  
Deep Learning Model

Abstract Automatic defect classification is vital to ensure product quality, especially for steel production. In the real world, the amount of collected samples with labels is limited due to high labor costs, and the gathered dataset is usually imbalanced, making accurate steel defect classification very challenging. In this paper, a novel deep learning model for imbalanced multi-label surface defect classification, named ImDeep, is proposed. It can be deployed easily in steel production lines to identify different defect types on the steel's surface. ImDeep incorporates three key techniques, i.e., Imbalanced Sampler, Fussy-FusionNet, and Transfer Learning. It improves the model's classification performance with multi-label and reduces the model's complexity over small datasets with low latency. The performance of different fusion strategies and three key techniques of ImDeep is verified. Simulation results prove that ImDeep accomplishes better performance than the state-of-the-art over the public dataset with varied sizes. Specifically, ImDeep achieves about 97% accuracy of steel surface defect classification over a small imbalanced dataset with a low latency, which improves about 10% compared with that of the state-of-the-art.

Everlasting security of quantum key distribution with 1K-DWCDM and quadratic hash

2021 ◽  
Vol 21 (3&4) ◽  
pp. 0181-0202
Author(s):  
Khodakhast Bibak ◽  
Robert Ritchie ◽  
Behrouz Zolfaghari
Keyword(s):  
Hash Function ◽  
Quantum Key Distribution ◽  
Key Distribution ◽  
Privacy Amplification ◽  
Universal Hashing ◽  
Wide Range ◽  
Strong Property ◽  
Everlasting Security ◽  
Universal Hash Function ◽  
General Method

Quantum key distribution (QKD) offers a very strong property called everlasting security, which says if authentication is unbroken during the execution of QKD, the generated key remains information-theoretically secure indefinitely. For this purpose, we propose the use of certain universal hashing based MACs for use in QKD, which are fast, very efficient with key material, and are shown to be highly secure. Universal hash functions are ubiquitous in computer science with many applications ranging from quantum key distribution and information security to data structures and parallel computing. In QKD, they are used at least for authentication, error correction, and privacy amplification. Using results from Cohen [Duke Math. J., 1954], we also construct some new families of $\varepsilon$-almost-$\Delta$-universal hash function families which have much better collision bounds than the well-known Polynomial Hash. Then we propose a general method for converting any such family to an $\varepsilon$-almost-strongly universal hash function family, which makes them useful in a wide range of applications, including authentication in QKD.

scholarly journals A survey on compact features for visual content analysis

2016 ◽  
Vol 5 ◽  
Author(s):  
Luca Baroffio ◽  
Alessandro E. C. Redondi ◽  
Marco Tagliasacchi ◽  
Stefano Tubaro
Keyword(s):  
Content Analysis ◽  
Large Scale ◽  
Ad Hoc ◽  
State Of The Art ◽  
Large Body ◽  
Visual Features ◽  
Low Latency ◽  
Visual Content ◽  
Feature Encoding ◽  
Memory Footprint

Visual features constitute compact yet effective representations of visual content, and are being exploited in a large number of heterogeneous applications, including augmented reality, image registration, content-based retrieval, and classification. Several visual content analysis applications are distributed over a network and require the transmission of visual data, either in the pixel or in the feature domain, to a central unit that performs the task at hand. Furthermore, large-scale applications need to store a database composed of up to billions of features and perform matching with low latency. In this context, several different implementations of feature extraction algorithms have been proposed over the last few years, with the aim of reducing computational complexity and memory footprint, while maintaining an adequate level of accuracy. Besides extraction, a large body of research addressed the problem of ad-hoc feature encoding methods, and a number of networking and transmission protocols enabling distributed visual content analysis have been proposed. In this survey, we present an overview of state-of-the-art methods for the extraction, encoding, and transmission of compact features for visual content analysis, thoroughly addressing each step of the pipeline and highlighting the peculiarities of the proposed methods.

scholarly journals A New Design of Cryptographic Hash Function: Gear

2016 ◽  
Vol 1 (1) ◽  
Author(s):  
Abdulaziz M Alkandari ◽  
Khalil Ibrahim Alkandari ◽  
Imad Fakhri Alshaikhli ◽  
Mohammad A. AlAhmad
Keyword(s):  
Hash Function ◽  
Block Cipher ◽  
Hash Functions ◽  
Fixed Size ◽  
Compression Function ◽  
Cryptographic Hash Function ◽  
Mode Of Operation ◽  
Main Components ◽  
Map Data ◽  
And Diffusion

A hash function is any function that can be used to map data of arbitrary sizeto data of fixed size. A hash function usually has two main components: a permutationfunction or compression function and mode of operation. We will propose a new concretenovel design of a permutation based hash functions called Gear in this paper. It is a hashfunction based on block cipher in Davies-Meyer mode. It uses the patched version ofMerkle-Damgård, i.e. the wide pipe construction as its mode of operation. Thus, theintermediate chaining value has at least twice larger length than the output hash. Andthe permutations functions used in Gear are inspired from the SHA-3 finalist Grøestl hashfunction which is originally inspired from Rijndael design (AES). There is a very strongconfusion and diffusion in Gear as a result.

scholarly journals Where to go from here? New cross layer techniques for LTE Turbo-Code decoding at high code rates

2018 ◽  
Vol 16 ◽  
pp. 77-87 ◽  
Author(s):  
Stefan Weithoffer ◽  
Norbert Wehn
Keyword(s):  
Turbo Codes ◽  
State Of The Art ◽  
Turbo Code ◽  
System Level ◽  
Cross Layer ◽  
High Area ◽  
Wide Range ◽  
Block Level ◽  
Hardware Architectures ◽  
Block Sizes

Abstract. The wide range of code rates and code block sizes supported by todays wireless communication standards, together with the requirement for a throughput in the order of Gbps, necessitates sophisticated and highly parallel channel decoder architectures. Code rates specified in the LTE standard, which uses Turbo-Codes, range up to r=0.94 to maximize the information throughput by transmitting only a minimum amount of parity information, which negatively impacts the error correcting performance. This especially holds for highly parallel hardware architectures. Therefore, the error correcting performance must be traded-off against the degree of parallel processing. State-of-the-art Turbo-Code decoder hardware architectures are optimized on code block level to alleviate this trade-off. In this paper, we follow a cross-layer approach by combining system level knowledge about the rate-matching and the transport block structure in LTE with the bit-level technique of on-the-fly CRC calculation. Thereby, our proposed Turbo-Code decoder hardware architecture achieves coding gains of 0.4–1.8 dB compared to state-of-the-art accross a wide range of code block sizes. For the fully LTE compatible Turbo-Code decoder, we demonstrate a negligible hardware overhead and a resulting high area and energy efficiency and give post place and route synthesis numbers.

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