【Author】 Kar, Suparna Khan, P. Kaif Ali Nalawade, Ravi Surendra Shounik, Vanga Aravind Patil, Vikas Ravi Kataoka, Kotaro
【影响因子】7.307
【主题类别】
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【Abstract】Due to the limited storage capacity of Internet of Things (IoT) devices, the use of third-party cloud storage service is an integral part of IoT based systems. Ensuring data integrity in cloud storage services is paramount for maintaining the safety and trustworthiness of the data generated and consumed by IoT applications. While verifying data integrity through defective data detection, the number of False Positives and False Negatives should be fewer so that the resolution is higher. However, increasing the resolution also incurs an increase in meta-data for integrity verification and results in higher storage overhead. This paper proposes High Resolution and Lightweight Defective Data Detection (HRL-D3) for IoT data integrity with a short verification time, low storage overhead and minimal computational cost. HRL-D3 introduces 1) the use of Merkle Hash Tree and the novel concept of Intermediate Hash for enabling faster Data Integrity Verification (DIV) and higher resolution, and 2) an Adaptive Data Chunking Algorithm for balancing the trade-off between resolution and storage overhead. Our security analysis examined the risks of potential attacks to HRL-D3, and outlined the prevention provided by the proposed solution as well as the mitigation through an operational workaround. A Proof of Concept implementation HRL-D3 was evaluated and demonstrated its effectiveness in balancing the trade off between the resolution and the storage overhead tradeoff as well as achieving low-latency DIV.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Defective data detection; DAG-based distributed ledger technology; Cloud storage; Internet of Things; Merkle hash tree; KL divergence; Gradient descent
【发表时间】2026
【收录时间】2025-09-16
【文献类型】
【影响因子】2.303
【主题类别】
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【Abstract】Move is a new programming language for smart contracts, known for making security its primary goal. However, several recent studies, reports, and other relevant materials have identified potential security concerns associated with Move. In this paper, we systematically collect and analyze a range of audit reports, blog posts, and bounty challenges related to Move. Through this analysis, we identify four types of vulnerabilities that have the potential to cause significant financial losses but have not been adequately addressed or explored in prior studies. For instance, one of the identified vulnerabilities enables attackers to gain the ability to issue tokens. To assist developers in understanding and mitigating these vulnerabilities, this paper provides a detailed description, illustrative examples, potential impacts, and mitigation recommendations for each vulnerability. Furthermore, to enable automated detection, we developed four new detectors based on MoveScan, the most advanced analysis framework for Move smart contracts. Using these four detectors, we identify up to 20,778 vulnerabilities across 37,302 contracts deployed on the Aptos and Sui, two of the most popular blockchains using Move. Through manual inspection, we find that our detectors achieve an overall precision rate of 98.82% and uncover real, impactful vulnerabilities. We performed formal verification of two vulnerabilities using Move Prover. Compared to the vulnerabilities identified by MoveScan, Move Prover achieved a relative recall rate of 78.95%. The novel findings presented in this paper offer valuable insights that empower developers to effectively detect and prevent these vulnerabilities using our proposed detectors, thereby contributing to the future improvement of Move contract security.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Move language; Smart contract; Vulnerability detection; Security; Blockchain
【发表时间】2025
【收录时间】2025-09-16
【文献类型】
【Author】 Alexander, R. Kumar, K. Pradeep Mohan
【影响因子】2.303
【主题类别】
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【Abstract】Multistage malware poses a significant and evolving threat to Internet of Things (IoT) devices. These threats can range from relatively simple attacks to more sophisticated operations, such as cryptojacking-where attackers exploit system resources for cryptocurrency mining-and Distributed Denial-of-Service (DDoS) attacks, which aim to overwhelm devices and networks, causing service disruptions. One major challenge in addressing these threats lies in the reliance on machine learning and deep learning solutions. These approaches often encounter difficulties due to imbalanced data samples, which can distort detection results, and limited generalization capability, a phenomenon known as model drift. Model drift occurs when a model trained on historical data fails to adapt to new and evolving attack patterns, thereby significantly limiting the effectiveness of intrusion detection systems. To confront these challenges, a novel approach called BoTSIAM-DRL is suggested. This innovative model combines Siamese active learning-a technique that utilizes similar input pairs to enhance understanding-with a reward mechanism that incentivizes accurate detection. This unique combination provides a fresh perspective and a solution not previously explored in existing literature. The design of BoTSIAM-DRL allows it to dynamically learn and adapt to the evolving nature of malware attacks, refining its strategies as new threats emerge. The model's performance has been rigorously evaluated using the MedBIoT and N-BaIoT datasets, which are specifically curated for IoT security challenges. Impressively, BoTSIAM-DRL has achieved a detection accuracy exceeding 99% throughout the entire lifecycle of these datasets, highlighting its potential as a robust defense mechanism against the increasingly sophisticated landscape of multistage malware threats targeting IoT devices.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Deep reinforcement learning (DRL); Matching siamese active learning (MSAL); Data handler (DL); Bashlite, Mirai, Torii, Botnet detection using a few shot active matching siamese network deep reinforcement learning (BoTSIAM); Deep Q Network (DQN)
【发表时间】2025
【收录时间】2025-09-16
【文献类型】
【Author】 Feng, Libo Wu, Peng Hu, Kai Yao, Shaowen
【影响因子】2.303
【主题类别】
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【Abstract】Recent advancements in blockchain technology have heightened interest in enabling information transfer and value exchange across different blockchains. To address asset and data interoperability challenges, cross-chain technology has emerged, though it often risks transaction privacy leakage. This paper presents a relay chain-based cross-chain model that facilitates operations through the relay chain while storing generated information on-chain, ensuring traceability. A privacy protection scheme and a verifiable multi-node key-sharing method are proposed, employing cryptographic techniques to safeguard transaction privacy. In case of disputes, privacy information can be decrypted via the relay chain for auditability. The paper includes a detailed analysis and performance testing of the proposed solution, comparing it with other existing privacy-preserving relay chain solutions, and evaluates the delay performance of the key-sharing algorithm, showcasing its security and feasibility advantages.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Relay chain; Privacy protection; Key sharing; Auditability
【发表时间】2025
【收录时间】2025-09-16
【文献类型】
【Author】 Luguterah, Austin Wontepaga
【影响因子】2.180
【主题类别】
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【Abstract】The meteoric rise of electronic sports (e-sports) has transformed competitive gaming into a platform for geopolitical influence, cultural diplomacy, and digital governance. This article explores how e-sports reshape international relations and soft power, using frameworks from international relations, cultural studies, and political economy. It highlights how states like South Korea, China, Russia, and Arabian Peninsula leverage e-sports to project cultural capital, while Western markets promote corporate-led models that extend platform capitalism. It examines tensions between state-driven cyber sovereignty and corporate control over digital infrastructure. Regional dynamics from Southeast Asian cooperation to U.S.-China tech rivalries highlight e-sports' role in economic positioning and international relations. As AI and blockchain reshape gaming's future, the article calls for deeper inquiry into e-sports' implications for global governance, digital citizenship, and cultural diplomacy.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】geopolitical; e-sports; soft power; diplomacy; cyber sovereignty
【发表时间】2025
【收录时间】2025-09-16
【文献类型】
【Author】 He, Shanshan Liu, Zhengyang
【影响因子】1.512
【主题类别】
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【Abstract】Objective: To explore the alleviating effect of digital supply chain finance (DSCF) on financing constraints experienced by small- and medium-sized enterprises (SMEs), with a view to promoting the digital transformation of enterprises. Methods: This observational study utilizes data from Chinese listed enterprises. The study's primary focus is on a selection of SRDI (abbreviation for "specialized, refined, distinctive, and innovative") enterprises in the electronics and machinery industries from 2013 to 2020. The study measures the level of DSCF in the regions where they are located, aims to empirically examine the role of DSCF in alleviating financing constraints for enterprises. Results: (1) SRDI enterprises in China continue to face persistent financing constraints, characterized by limited access to working capital and restricted credit availability. (2) Empirical analysis demonstrates that DSCF can alleviate these financing constraints. (3) Notably, the mitigation effect exhibits industry-specific heterogeneity between the electronics and manufacturing industries, likely attributable to differences in supply chain complexity and asset tangibility between these sectors. Conclusions: Findings underscore DSCF's critical role in alleviating the financing constraints of SMEs while informing targeted financial ecosystem reforms. We propose enhanced policy interventions: (1) tax incentives and blockchain-enabled data-sharing mechanisms to dismantle information asymmetries and boost DSCF efficiency; and (2) sector-specific solutions addressing electronics' R&D liquidity challenges and machinery's capital-intensive production cycles through optimized DSCF frameworks.
你可以尝试使用大模型来生成摘要 立即生成
【Keywords】Digital supply chain finance; financing constraints; SRDI enterprises; digital intelligence enabling; SME
【发表时间】2025
【收录时间】2025-09-16
【文献类型】