Previous studies have revealed that Bitcoin’s anonymity is not absolute. Coin mixing protocols have been proposed to address these anonymity issues by breaking or obfuscating the relationship between transaction inputs and outputs, thereby ensuring privacy. Due to their ability to enhance anonymity, these protocols are often associated with illegal money laundering activities, and some mixing services have faced sanctions. This paper examines coin mixing protocols by analyzing the techniques they employ to obscure input-output relationships. Furthermore, it explorers the potential threats to which mixing protocols may be exposed and provides a comprehensive analysis of their vulnerabilities.

Managing identity is a crucial issue, and with the advent of digital identity, Self-Sovereign Identity (SSI) has been highlighted. SSI allows the owner to have sovereignty over their identity information. Currently, blockchain technology is widely used to implement SSI management system. Issuing a verifiable credential (VC) based on blockchain has two advantages: it ensures the VC has not been tampered with and makes the VC trustworthy by sharing the same ledger among untrusted parties. This paper presents a SSI management system which was designed and implemented for police or firefighters who still manage identity information centrally. Furthermore, given the inherent risks associated with these occupations, it is imperative to have a secure healthcare system to meet their specific needs. We propose a system that links these healthcare systems, allowing owners of identity information to monitor how their identity information has been used. The usage history of the system is stored in a permissioned blockchain, specifically Hyperledger Fabric.

With the advent of e-commerce and electronic payment systems, the use of paper currency is decreasing. Therefore, it is sufficiently predictable that most paper currencies will disappear and digital currencies will become the mainstream. This phenomenon is further accelerated by advances in blockchain technology and COVID-19. This is why the Central Bank Digital Currency (CBDC) has recently begun to attract attention. Currently, there are studies on CBDC with a blockchain-based distributed ledger. In this paper, we propose Cosmos blockchain based CBDC (Cos-CBDC) that enables communication between blockchains using Inter-Blockchain Communication (IBC) protocol to ensure interoperability. We not only analyze the requirements of Cos-CBDC but also design and implement it using Cosmos-SDK. Furthermore, we propose a Group Key Management system in Cos-CBDC. It can give different user privileges, and privacy-preserving is possible in the key generation process.

This paper presents a region-based active contour method that embeds both region and gradient information. In the proposed algorithm area term practices a new region-based signed pressure force (SPF) function which utilizes the image local information obtained using the local binary fitted (LBF) energy model. By introducing the SPF function based on local fitted image (LFI), the proposed model is able to segment images with intensity in homogeneities. A Gaussian kernel is used to regularize the level set function which not only regularizes it but also removes the need of computationally expensive re-initialization. The proposed segmentation algorithm is applied to synthetic and real images in order to demonstrate the accuracy, effectiveness, and robustness of the algorithm.

This paper presents an effective object tracking algorithm for simultaneous changes, such as deformation, translation, scale, and color variations. The proposed algorithm is based on the maximum color distance (MCD) and the shape density. The MCD provides invariance for illuminations changes, while the shape density is the density of shape distribution corresponding to the respective distance from the center position of an object. The generated probability density function (PDF) of shape density is invariant for object orientation and robust to deformable object and linear scale variation. The initialized model of a target for PDF of the MCD and shape density is compared with candidates by Least Mean Square Error in a next frame. Experimental results show that the tracking system using the proposed algorithm with the MCD and the shape density provides effective results for simultaneous changes in target such as translation, deformation, scale and color variations.

In this correspondence, the characteristic polynomial and hence the linear complexity of Hall's sextic residue sequences are determined.