Batsmen are accorded a certain precedence for better batting ability over their peers. The batsmen in cricket are assessed mostly based on their batting average. However, comparing players by batting average over different timelines does not yield the appropriate results, as the batting productivity of a particular player varies in unique ways across the different formats of the game. Using batting averages for comparison does not include factors such as the speed of scoring runs and the frequency of milestones achieved. The objective of this study is to present an effective knowledge-based mechanism for judging and comparing the batting strength of players in different formats of cricket. This methodology uses a complex network consisting of effective features that are subsequently integrated to formulate a Batting Precedence Score, which is further incorporated into an efficient Batting Precedence Score algorithm. In addition, we created a structured World Wide Batsman Dataset (WWBD) for our analysis based on the ESPN Cricinfo dataset. The results of extensive experiments demonstrate that the proposed method provides promising insights. The batting precedence of the proposed method is further compared with those of existing methods, and the proposed method displays better results.

Hardy’s paradox (equivalently, Hardy’s non-locality or Hardy’s test) [Phys. Rev. Lett. 68, 2981 (1992)] is used to show non-locality without inequalities, and it has been tested several times using optical circuits. We, for the first time, experimentally test Hardy’s paradox of non-locality in superconducting qubits. For practical verification of Hardy’s paradox, we argue that the error-modeling used in optical circuits is not useful for superconducting qubits. So, we propose a new error-modeling for Hardy’s paradox and a new method to estimate the lower bound on Hardy’s probability (i.e., the probability of a specific event in Hardy’s test) for superconducting qubits. Our results confirmed the theory that any non-maximally entangled state of two qubits violates Hardy’s equations; whereas, any maximally entangled state and product state of two qubits do not exhibit Hardy’s non-locality. Further, we point out the difficulties associated with the practical implementation of quantum protocols based on Hardy’s paradox and propose possible remedies. We also propose two performance measures for any two qubits of any quantum computer based on superconducting qubits.

We present RC4-AccSuite, a hardware accelerator, which combines the flexibility of an application specific instruction set processor and the performance of an application specific IC for the most widely deployed commercial stream cipher RC4 and its eight prominent variants, including Spritz (CRYPTO-2014 Rump-session). Our carefully designed instruction set architecture reuses combinational and sequential logic at its various pipeline stages and memories, saving up to 41% in terms of area, compared with the individual cores, while the power budget being dictated primarily by the variant used. Moreover, using state replication, noticeable throughput performance enhancement in RC4 variants is achieved. RC4-AccSuite possesses extensibility for future variants of RC4 with little or no tweaking.

With increasing usage of hardware accelerators in modern heterogeneous System-on-Chips (SoCs), the distinction between hardware and software is no longer rigid. The domain of cryptography is no exception and efficient hardware design of so-called software ciphers are becoming increasingly popular. In this paper, for the first time we propose an efficient hardware accelerator design for SOSEMANUK, one of the finalists of the eSTREAM stream cipher competition in the software category. Since SOSEMANUK combines the design principles of the block cipher Serpent and the stream cipher SNOW 2.0, we make our design flexible to accommodate the option for independent execution of Serpent and SNOW 2.0. In the process, we identify interesting design points and explore different levels of optimizations. We perform a detailed experimental evaluation for the performance figures of each design point. The best throughput achieved by the combined design is 67.84 Gbps for SOSEMANUK, 33.92 Gbps for SNOW 2.0 and 2.12 Gbps for Serpent. Our design outperforms all existing hardware (as well as software) designs of Serpent, SNOW 2.0 and SOSEMANUK, along with those of all other eSTREAM candidates.

We present RunStream, a rapid prototyping framework for realizing stream cipher implementations based on algorithmic specifications and architectural customizations desired by the users. In the dynamic world of cryptography where newer recommendations are frequently proposed, the need of such tools is imperative. It carries out design validation and generates an optimized software implementation and a synthesizable Register Transfer Level Verilog description. Our framework enables speedy benchmarking against critical resources like area, throughput, power, and latency and allows exploration of alternatives. Using RunStream, we successfully implemented various stream ciphers and benchmarked the quality of results to be at par with published hand-optimized implementations.

Cryptographic coprocessors are inherent part of modern System-on-Chips. It serves dual purpose - efficient execution of cryptographic kernels and supporting protocols for preventing IP-piracy. Flexibility in such coprocessors is required to provide protection against emerging cryptanalytic schemes and to support different cryptographic functions like encryption and authentication. In this context, a novel crypto-coprocessor, named CoARX, supporting multiple cryptographic algorithms based on Addition (A), Rotation (R) and eXclusive-or (X) operations is proposed. CoARX supports diverse ARX-based cryptographic primitives. We show that compared to dedicated hardware implementations and general-purpose microprocessors, it offers excellent performance-flexibility trade-off including adaptability to resist generic cryptanalysis.

A novel technique for cryptanalysis of the stream cipher Grain-v1 is given. In a particular setting, the algorithms proposed in this study provide recovery of an internal state of Grain-v1 with the expected time complexity of only 254 table look-up operations employing a memory of dimension ∼270, assuming availability of 234 keystream sequences each of length 238 generated for different initial values, and the pre-processing time complexity of ∼288. These figures appear as significantly better in comparison with the previously reported ones. The proposed approach for cryptanalysis primarily depends on the order of normality of the employed Boolean function in Grain-v1. Accordingly, in addition to the security evaluation insights of Grain-v1, the results of this study are also an evidence of the cryptographic significance of the normality criteria of Boolean functions.

A Boolean function is k-normal if it is constant on a k-dimensional flat of its domain. This paper demonstrates that k-normality of a Boolean function can be exploited to mount a dedicated algebraic attack on a stream cipher of the nonlinear filter generator type, which employs a k-normal Boolean function as its filter function. The cryptanalysis is based on the possibility for pre-computing a table of the state-key stream pairs via solving certain system of algebraic equations as a consequence of the employed k-normal Boolean function. This pre-computed table is the main origin for mounting the cryptanalysis and it is independent of a the sample for cryptanalysis and the secret key employed for generating the sample.

Steganography involves hiding messages in innocuous media such as images, while steganalysis is the field of detecting these secret messages. The ultimate goal of steganalysis is two-fold: making a binary classification of a file as stego-bearing or innocent, and secondly, locating the hidden message with an aim to extracting, sterilizing or manipulating it. Almost all steganalysis approaches (known as attacks) focus on the first of these two issues. In this paper, we explore the difficult related problem: given that we know an image file contains steganography, locate which pixels contain the message. We treat the hidden message location problem as outlier detection using probability/energy measures of images motivated by the image restoration community. Pixels contributing the most to the energy calculations of an image are deemed outliers. Typically, of the top third of one percent of most energized pixels (outliers), we find that 87% are stego-bearing in color images and 61% in grayscale images. In all image types only 1% of all pixels are stego-bearing indicating our techniques provides a substantial lift over random guessing.