Zobrazeno 1 - 10
of 1 139
pro vyhledávání: '"Hoang, Dinh"'
Autor:
Manh, Bui Duc, Nguyen, Chi-Hieu, Hoang, Dinh Thai, Nguyen, Diep N., Zeng, Ming, Pham, Quoc-Viet
This work proposes a novel privacy-preserving cyberattack detection framework for blockchain-based Internet-of-Things (IoT) systems. In our approach, artificial intelligence (AI)-driven detection modules are strategically deployed at blockchain nodes
Externí odkaz:
http://arxiv.org/abs/2412.13522
Jointly optimizing power allocation and device association is crucial in Internet-of-Things (IoT) networks to ensure devices achieve their data throughput requirements. Device association, which assigns IoT devices to specific access points (APs), cr
Externí odkaz:
http://arxiv.org/abs/2411.10082
The integration of the Metaverse into a human-centric ecosystem has intensified the need for sophisticated Human Digital Twins (HDTs) that are driven by the multifaceted human data. However, the effective construction of HDTs faces significant challe
Externí odkaz:
http://arxiv.org/abs/2410.23639
Autor:
Van Huynh, Nguyen, Zhang, Bolun, Tran, Dinh-Hieu, Hoang, Dinh Thai, Nguyen, Diep N., Zheng, Gan, Niyato, Dusit, Pham, Quoc-Viet
Spectrum access is an essential problem in device-to-device (D2D) communications. However, with the recent growth in the number of mobile devices, the wireless spectrum is becoming scarce, resulting in low spectral efficiency for D2D communications.
Externí odkaz:
http://arxiv.org/abs/2410.17971
This paper introduces a novel lossless compression method for compressing geometric attributes of point cloud data with bits-back coding. Our method specializes in using a deep learning-based probabilistic model to estimate the Shannon's entropy of t
Externí odkaz:
http://arxiv.org/abs/2410.18115
Autor:
Bui, Nhat-Tan, Hoang, Dinh-Hieu, Trinh, Quoc-Huy, Tran, Minh-Triet, Nguyen, Truong, Gauch, Susan
Negation is a fundamental linguistic concept used by humans to convey information that they do not desire. Despite this, there has been minimal research specifically focused on negation within vision-language tasks. This lack of research means that v
Externí odkaz:
http://arxiv.org/abs/2409.06481
This paper presents a novel Collaborative Cyberattack Detection (CCD) system aimed at enhancing the security of blockchain-based data-sharing networks by addressing the complex challenges associated with noise addition in federated learning models. L
Externí odkaz:
http://arxiv.org/abs/2409.04972
The ability to estimate 3D movements of users over edge computing-enabled networks, such as 5G/6G networks, is a key enabler for the new era of extended reality (XR) and Metaverse applications. Recent advancements in deep learning have shown advantag
Externí odkaz:
http://arxiv.org/abs/2409.00087
This paper aims to propose a novel framework to address the data privacy issue for Federated Learning (FL)-based Intrusion Detection Systems (IDSs) in Internet-of-Vehicles(IoVs) with limited computational resources. In particular, in conventional FL
Externí odkaz:
http://arxiv.org/abs/2407.18503
Autor:
Son, Do Hai, Manh, Bui Duc, Khoa, Tran Viet, Trung, Nguyen Linh, Hoang, Dinh Thai, Minh, Hoang Trong, Alem, Yibeltal, Minh, Le Quang
Blockchain-based supply chain (BSC) systems have tremendously been developed recently and can play an important role in our society in the future. In this study, we develop an anomaly detection model for BSC systems. Our proposed model can detect cyb
Externí odkaz:
http://arxiv.org/abs/2407.15603