A New Stream Cipher HC-256

HC-256 is a software-efficient stream cipher. It generates keystream from a 256-bit secret key and a 256-bit initialization vector. The encryption speed of the C implementation of HC-256 is about 1.9 bits per clock cycle (4.2 cycle/byte) on the Intel Pentium 4 processor. A variant of HC-256 is also introduced in this paper

Cryptanalysis of a 32-bit RC4-like Stream Cipher

Nawaz, Gupta and Gong recently proposed a 32-bit RC4-like stream cipher. In this paper, we show that the keystream generated from their stream cipher is not random. The keystream can be distinguished from random with only about 100 outputs (3200 bits) in 2 milliseconds on Intel Centrino 1.6GHz processor

Breaking the Stream Cipher Whitenoise

Whitenoise is a stream cipher with specification given at http://eprint.iacr.org/2003/249. In this paper, we show that Whitenoise is extremely weak. It can be broken by solving about 80,000 linear equations. And only about 80,000 bytes keystream are needed in the attack

Funding Liquidity Shocks in a Quasi-Experiment: Evidence from the CDS Big Bang

A major change in trading conventions in April 2009, the so-called “CDS Big Bang,” induces upfront fees for trading North American CDSs. Exploiting this quasi-experiment, we provide evidence that upfront fees have a differential effect on CDS bid-ask spreads across CDS premiums. Furthermore, the funding effect is stronger for CDS contracts on smaller and riskier firms, contracts with longer maturities, and non-centrally-cleared contracts. The effect also becomes stronger after Deutsche Bank exits the CDS market. Finally, we find similar results using European CDSs. Our experimental setting offers new economic insights on the quantification and mechanism of the funding liquidity effect

Chinese merchant group culture, corporate social responsibility, and cost of debt : evidence from private listed firms in China

Chinese merchant groups are commercial organizations that have developed over thou-sands of years. Given the importance of private firms to China’s sustainable development, this study investigates the impact of the traditional Chinese concept of merchant groups on corporate social responsibility (CSR) performance and cost of debt, using Chinese private listed firms during 2008–2020. We measure merchant group culture based on the company’s geographic location. Ordi-nary least squares regression models are used to test the hypotheses. According to the results, the CSR performance of firms from five traditional Chinese merchant groups is better than non-members. A positive relationship exists between the strength of merchant group culture and CSR performance; this relationship is stronger among merchant group companies. The closer the culture to CSR values, the better the CSR performance, which is negatively related to the cost of debt. The findings are in line with the peer effect theory. Therefore, the study provides evidence that it is essential to consider the traditional Chinese merchant group culture for firms’ CSR strategies beyond formal financial and regulatory factors in China. This study is a first step in exploring the impact of merchant group culture in China on CSR performance and the economic application of this relationship

Characterization of Oil Droplets in the Upper Cavity of a Rotary Compressor

The lubricant oil is used to lubricate the bearings and seal the clearance between the sliding parts in the rotary compressor equipped in an air conditioning system. However, a portion of the oil is atomized and exhausted with the refrigerant flow, which reduces the system’s efficiency and reliability. In this study, a highresolution shadowgraph system is applied to a modified rotary compressor to visualize the oil droplets in its upper cavity. The oil droplet size distribution is studied statistically at different radial locations and different crankshaft’s frequencies. It is observed that more oil droplets with larger D10 and D32 are generated as the rotating frequency increases. There are fewer droplets moving toward the center of the compressor. More oil droplets in the upper cavity at higher frequency might increase the Oil Discharge Rate (ODR) if these droplets are carried into the downstream discharge tube. On the other hand, larger droplets at a higher frequency may reduce ODR since the appropriate aerodynamic design may retain these droplets in the upper cavity without moving into the discharge tube. The result can assist designers in improving the CFD analysis of compressors and ultimately reducing ODR

A Diffusion model for POI recommendation

Next Point-of-Interest (POI) recommendation is a critical task in location-based services that aim to provide personalized suggestions for the user's next destination. Previous works on POI recommendation have laid focused on modeling the user's spatial preference. However, existing works that leverage spatial information are only based on the aggregation of users' previous visited positions, which discourages the model from recommending POIs in novel areas. This trait of position-based methods will harm the model's performance in many situations. Additionally, incorporating sequential information into the user's spatial preference remains a challenge. In this paper, we propose Diff-POI: a Diffusion-based model that samples the user's spatial preference for the next POI recommendation. Inspired by the wide application of diffusion algorithm in sampling from distributions, Diff-POI encodes the user's visiting sequence and spatial character with two tailor-designed graph encoding modules, followed by a diffusion-based sampling strategy to explore the user's spatial visiting trends. We leverage the diffusion process and its reversed form to sample from the posterior distribution and optimized the corresponding score function. We design a joint training and inference framework to optimize and evaluate the proposed Diff-POI. Extensive experiments on four real-world POI recommendation datasets demonstrate the superiority of our Diff-POI over state-of-the-art baseline methods. Further ablation and parameter studies on Diff-POI reveal the functionality and effectiveness of the proposed diffusion-based sampling strategy for addressing the limitations of existing methods