Zobrazeno 41 - 50
of 340
pro vyhledávání: '"Thai, My T."'
Autor:
Nguyen, Truc, Thai, My T.
Publikováno v:
IEEE Transactions on Computers, vol. 72, no. 3, pp. 641-652, 1 March 2023
Since 2016, sharding has become an auspicious solution to tackle the scalability issue in legacy blockchain systems. Despite its potential to strongly boost the blockchain throughput, sharding comes with its own security issues. To ease the process o
Externí odkaz:
http://arxiv.org/abs/2007.08600
Autor:
Nguyen, Truc D. T., Thai, My T.
Although the iterative double auction has been widely used in many different applications, one of the major problems in its current implementations is that they rely on a trusted third party to handle the auction process. This imposes the risk of sin
Externí odkaz:
http://arxiv.org/abs/2007.08595
A major challenge in blockchain sharding protocols is that more than 95% transactions are cross-shard. Not only those cross-shard transactions degrade the system throughput but also double the confirmation time, and exhaust an already scarce network
Externí odkaz:
http://arxiv.org/abs/2007.08596
Autor:
Pan, Tianyi, Mishra, Subhankar, Nguyen, Lan N., Lee, Gunhee, Kang, Jungmin, Seo, Jungtaek, Thai, My T.
Publikováno v:
IEEE Access 5 (2017): 16774-16783
Social Networks (SNs) have been gradually applied by utility companies as an addition to smart grid and are proved to be helpful in smoothing load curves and reducing energy usage. However, SNs also bring in new threats to smart grid: misinformation
Externí odkaz:
http://arxiv.org/abs/2005.08705
Cost-aware Targeted Viral Marketing (CTVM), a generalization of Influence Maximization (IM), has received a lot of attentions recently due to its commercial values. Previous approximation algorithms for this problem required a large number of samples
Externí odkaz:
http://arxiv.org/abs/1910.04134
In this work, we study the Submodular Cost Submodular Cover problem, which is to minimize the submodular cost required to ensure that the submodular benefit function exceeds a given threshold. Existing approximation ratios for the greedy algorithm as
Externí odkaz:
http://arxiv.org/abs/1908.00653
In many modern image-classification applications, understanding the cause of model's prediction can be as critical as the prediction's accuracy itself. Various feature-based local explanations generation methods have been designed to give us more ins
Externí odkaz:
http://arxiv.org/abs/1906.02032
In this paper, we propose a novel Heterogeneous Gaussian Mechanism (HGM) to preserve differential privacy in deep neural networks, with provable robustness against adversarial examples. We first relax the constraint of the privacy budget in the tradi
Externí odkaz:
http://arxiv.org/abs/1906.01444
In this paper, we aim to develop a scalable algorithm to preserve differential privacy (DP) in adversarial learning for deep neural networks (DNNs), with certified robustness to adversarial examples. By leveraging the sequential composition theory in
Externí odkaz:
http://arxiv.org/abs/1903.09822
In this paper, we explore the partitioning attacks on the Bitcoin network, which is shown to exhibit spatial bias, and temporal and logical diversity. Through data-driven study we highlight: 1) the centralization of Bitcoin nodes across autonomous sy
Externí odkaz:
http://arxiv.org/abs/1902.03636