Payment Channel networks (PCNs), pivotal for blockchain scalability, facilitate multiple off-chain payments between any two users. They utilize scripts to define and execute payment conditions in various blockchains, ...
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Payment Channel networks (PCNs), pivotal for blockchain scalability, facilitate multiple off-chain payments between any two users. They utilize scripts to define and execute payment conditions in various blockchains, but this poses privacy, efficiency, and compatibility challenges. To overcome these, scriptless cleverly embeds payment conditions into digital signatures instead of complex scripts. Cryptography effectively safeguards the construction and publication of transactions in script-based and scriptless PCNs. Although several surveys analyze PCN protocols, only a few discuss their underlying scripting languages and even none explore the cryptography involved. This survey is the first to comprehensively overview cryptography in PCNs from scripting perspectives, filling the existing knowledge void. Our analysis offers a complete picture of script-based and scriptless protocols and their coexistence. We then explore advanced cryptographic primitives in both categories, systematically studying these for the first time, and demonstrate their instantiations in atomic swaps. Finally, we research vast related surveys and provide a future-oriented outlook.
With the emergence of edge computing, there’s a growing need for advanced technologies capable of real-time, efficient processing of complex data on edge devices, particularly in mobile health systems handling pathol...
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With the emergence of edge computing, there’s a growing need for advanced technologies capable of real-time, efficient processing of complex data on edge devices, particularly in mobile health systems handling pathological images. On edge computing devices, the lightweighting of models and reduction of computational requirements not only save resources but also increase inference speed. Although many lightweight models and methods have been proposed in recent years, they still face many common challenges. This paper introduces a novel convolution operation, Dynamic Scalable Convolution (DSC), which optimizes computational resources and accelerates inference on edge computing devices. DSC is shown to outperform traditional convolution methods in terms of parameter efficiency, computational speed, and overall performance, through comparative analyses in computer vision tasks like image classification and semantic segmentation. Experimental results demonstrate the significant potential of DSC in enhancing deep neural networks, particularly for edge computing applications in smart devices and remote healthcare, where it addresses the challenge of limited resources by reducing computational demands and improving inference speed. By integrating advanced convolution technology and edge computing applications, DSC offers a promising approach to support the rapidly developing mobile health field, especially in enhancing remote healthcare delivery through mobile multimedia communication.
Multi-modal sarcasm detection involves determining whether a given multi-modal input conveys sarcastic intent by analyzing the underlying sentiment. Recently, vision large language models have shown remarkable success...
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Multi-modal sarcasm detection involves determining whether a given multi-modal input conveys sarcastic intent by analyzing the underlying sentiment. Recently, vision large language models have shown remarkable success on various of multi-modal tasks. Inspired by this, we systematically investigate the impact of vision large language models in zero-shot multi-modal sarcasm detection task. Furthermore, to capture different perspectives of sarcastic expressions, we propose a multi-view agent framework, S3 Agent, designed to enhance zero-shot multi-modal sarcasm detection by leveraging three critical perspectives: superficial expression, semantic information, and sentiment expression. Our experiments on the MMSD2.0 dataset, which involves six models and four prompting strategies, demonstrate that our approach achieves state-of-the-art performance. Our method achieves an average improvement of 13.2% in accuracy. Moreover, we evaluate our method on the text-only sarcasm detection task, where it also surpasses baseline approaches.
This book presents the proceedings of the Third International Conference on Trust, Privacy and security in Digital Business (TrustBus 2006), held in Kraków, Poland, September 5-7, 2006. The conference continues f...
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ISBN:
(数字)9783540377528
ISBN:
(纸本)9783540377504
This book presents the proceedings of the Third International Conference on Trust, Privacy and security in Digital Business (TrustBus 2006), held in Kraków, Poland, September 5-7, 2006. The conference continues from previous events held in Zaragoza (2004) and Copenhagen (2005), and maintains the aim of bringing together academic researchers and industry developers to discuss the state of the art in technology for establishing trust, privacy and security in digital business. We thank the attendees for coming to Kraków to participate and debate the new emerging advances in this area. The conference programme included two keynote presentations, one panel session and eight technical papers sessions. The keynote speeches were delivered by Jeremy Ward from Symantec EMEA on the topic of “Building the Information Assurance Community of Purpose”, and by Günter Karjoth from IBM Research - Zurich, with a talk entitled “Privacy Practices and Economics –– From Privacy Policies to Privacy SLAs. ” The subject of the panel discussion was “Is security Without Trust Feasible?” chaired by Leszek T. Lilien from Western Michigan University, USA. The reviewed paper sessions covered a broad range of topics, from access control models to security and risk management, and from privacy and identity management to security protocols. The conference attracted 70 submissions, each of which was assigned to four referees for review. The Programme Committee ultimately accepted 24 papers for inclusion, which were revised based upon comments from their reviews.
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